From suashdeb at gmail.com Sun Aug 1 04:53:11 2021 From: suashdeb at gmail.com (Suash Deb) Date: Sun, 1 Aug 2021 14:23:11 +0530 Subject: Connectionists: Announcement of ISCMI 2022 (Toronto, Canada) Message-ID: Dear colleagues, As already intimated that because of the circumstances beyond our control due to the prevailing covid situation, ISCMI 2021 will have to be conducted in *virtual mode *this year & that the deadline for the submission of manuscripts have been extended till *30th August'21. * Hope to meet many of you online during ISCMI21 this year http://iscmi.us/index.html Looking ahead, I would also like to let you know that *ISCMI 2022* will be held (hopefully physically) in *Toronto* next year. Attached pls. find a *preliminary leaflet *of the same. I solicit your help in disseminating this among your peers in advance. As you know that *since 2017*, this conference (our flagship one) is being held *in memory of Prof. Lotfi Zadeh* which includes among others the annual Memorial speech in his memory, delivered by one eminent scientist in our field http://www.iicci.in/speakers.html Stay safe & with best, Suash Deb General Chair, ISCMI 2022 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Leaflet - ISCMI2022.pdf Type: application/pdf Size: 576762 bytes Desc: not available URL: From suashdeb at gmail.com Sun Aug 1 04:50:29 2021 From: suashdeb at gmail.com (Suash Deb) Date: Sun, 1 Aug 2021 14:20:29 +0530 Subject: Connectionists: Announcement of ISCMI 2022 (Toronto, Canada) Message-ID: Dear colleagues, As already intimated that because of the circumstances beyond our control due to the prevailing covid situation, ISCMI 2021 will have to be conducted in *virtual mode *this year & that the deadline for the submission of manuscripts have been extended till *30th August'21. * Hope to meet many of you online during ISCMI21 this year http://iscmi.us/index.html Looking ahead, I would also like to let you know that *ISCMI 2022* will be held (hopefully physically) in *Toronto* next year. Attached pls. find a *preliminary leaflet *of the same. I solicit your help in disseminating this among your peers in advance. As you know that *since 2017*, this conference (our flagship one) is being held *in memory of Prof. Lotfi Zadeh* which includes among others the annual Memorial speech in his memory, delivered by one eminent scientist in our field http://www.iicci.in/speakers.html Stay safe & with best, Suash Deb General Chair, ISCMI 2022 -------------- next part -------------- An HTML attachment was scrubbed... URL: From george at cs.ucy.ac.cy Sun Aug 1 06:15:03 2021 From: george at cs.ucy.ac.cy (George A. Papadopoulos) Date: Sun, 1 Aug 2021 13:15:03 +0300 Subject: Connectionists: 2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (IEEE EAIS 2022): First Call for Papers and Special Sessions Message-ID: *** First Call for Papers and Special Sessions *** 2022 IEEE International Conference on Evolving and Adaptive Intelligent Systems (IEEE EAIS 2022) May 25-27, 2022, Golden Bay Hotel 5*, Larnaca, Cyprus http://cyprusconferences.org/eais2022/ (Proceedings to be published by the IEEE Xplore Digital Library; Special Journal Issue with Evolving Systems, Springer) IEEE EAIS 2022 will provide a working and friendly atmosphere and will be a leading international forum focusing on the discussion of recent advances, the exchange of recent innovations and the outline of open important future challenges in the area of Evolving and Adaptive Intelligent Systems. Over the past decade, this area has emerged to play an important role on a broad international level in today's real-world applications, especially those ones with high complexity and dynamic changes. Its embedded modelling and learning methodologies are able to cope with real-time demands, changing operation conditions, varying environmental influences, human behaviours, knowledge expansion scenarios and drifts in online data streams. Conference Topics Basic Methodologies Evolving Soft Computing Techniques. Evolving Fuzzy Systems. Evolving Rule-Based Classifiers. Evolving Neuro-Fuzzy Systems. Adaptive Evolving Neural Networks. Online Genetic and Evolutionary Algorithms. Data Stream Mining. Incremental and Evolving Clustering. Adaptive Pattern Recognition. Incremental and Evolving ML Classifiers. Adaptive Statistical Techniques. Evolving Decision Systems. Big Data. Problems and Methodologies in Data Streams Stability, Robustness, Convergence in Evolving Systems. Online Feature Selection and Dimension Reduction. Online Active and Semi-supervised Learning. Online Complexity Reduction. Computational Aspects. Interpretability Issues. Incremental Adaptive Ensemble Methods. Online Bagging and Boosting. Self-monitoring Evolving Systems. Human-Machine Interaction Issues. Hybrid Modelling, Transfer Learning. Reservoir Computing. Applications of EAIS Time Series Prediction. Data Stream Mining and Adaptive Knowledge Discovery. Robotics. Intelligent Transport and Advanced Manufacturing. Advanced Communications and Multimedia Applications. Bioinformatics and Medicine. Online Quality Control and Fault Diagnosis. Condition Monitoring Systems. Adaptive Evolving Controller Design. User Activities Recognition. Huge Database and Web Mining. Visual Inspection and Image Classification. Image Processing. Cloud Computing. Multiple Sensor Networks. Query Systems and Social Networks. Alternative Statistical and Machine Learning Approaches. Special Sessions Distinguished researchers working in theory, analysis and applications of evolving adaptive and intelligent systems and related areas are encouraged to submit proposals within the technical scope of IEEE EAIS 2022. Researchers interested in organising special sessions are invited to submit a formal proposal to the Special Sessions Chair Gabriella Casalino (gabriella.casalino at uniba.it) and to the General Chair George Angelos Papadopoulos (george at cs.ucy.ac.cy), by specifying: - Special Session Lead Organiser email address, details and mini-bio - Co-Organiser(s) details and mini-bio (optional) - Special Session title - Aim and scope of the Special Session (~half a page) - A list of main topics of the Special Session - A list of potential/expected contributors Submissions Submitted papers should not exceed 8 pages plus at most 2 pages overlength. Submissions of full papers are accepted online through Easy Chair (https://easychair.org/conferences/?conf=eais2022). The EAIS 2022 proceedings will be published on IEEE Xplore Digital Library. Authors of selected papers will be invited to submit extended versions for possible inclusion in a special issue of Evolving Systems - An Interdisciplinary Journal for Advanced Science and Technology (Springer). Important Dates ? Special Session submission: October 1, 2021 ? Special Session acceptance: October 10, 2021 ? Paper submission: January 10, 2022 ? Notification of acceptance/rejection: February 19, 2022 ? Camera ready submission: March 20, 2022 ? Authors registration: March 20, 2022 ? Conference Dates: May 25-27, 2022 Social Media FB: https://www.facebook.com/IEEEEAIS Twitter: https://twitter.com/IEEE_EAIS Linkedin: https://www.linkedin.com/events/2022ieeeconferenceonevolvingand6815560078674972672/ Organization Honorary Chairs ? Dimitar Filev, Ford Motor Co., USA ? Nikola Kasabov, Auckland University of Technology, New Zealand General Chairs ? George A. Papadopoulos, University of Cyprus, Nicosia, Cyprus ? Plamen Angelov, Lancaster University, UK Program Committee Chairs ? Giovanna Castellano, University of Bari, Italy ? Jos? A. Iglesias, Carlos III University of Madrid, Spain -------------- next part -------------- An HTML attachment was scrubbed... URL: From leslie.perez at pucv.cl Mon Aug 2 10:27:02 2021 From: leslie.perez at pucv.cl (Leslie Angelica Perez Caceres) Date: Mon, 2 Aug 2021 11:27:02 -0300 Subject: Connectionists: Second Call for Papers: EvoCOP 2022 - The 22nd European Conference on Evolutionary Computation in Combinatorial Optimisation Message-ID: (Apologies for cross-posting) ************************************************************************************* Second Call for Papers: EvoCOP 2022 - The 22nd European Conference on Evolutionary Computation in Combinatorial Optimisation http://www.evostar.org/2022/evocop/ April 20 - 22, 2022 held as part of EvoStar (http://www.evostar.org) Venue: *Somewhere On Earth!* ** EvoCOP is now CORE Rank B ** Submission deadline: November 1, 2021 ************************************************************************************* The 22nd European Conference on Evolutionary Computation in Combinatorial Optimisation is a multidisciplinary conference that brings together researchers working on applications and theory of evolutionary computation methods and other metaheuristics for solving difficult combinatorial optimisation problems appearing in various industrial, economic, and scientific domains. Successfully solved problems include, but are not limited to, multi-objective, uncertain, dynamic and stochastic problems in the context of scheduling, timetabling, network design, transportation and distribution, vehicle routing, stringology, graphs, satisfiability, energy optimisation, cutting, packing, planning and search-based software engineering. The EvoCOP 2021 conference will be held somewhere on Earth, together with EuroGP (the 24th European Conference on Genetic Programming), EvoMUSART (the 10th European conference on evolutionary and biologically inspired music, sound, art and design) and EvoApplications (the 24th European Conference on the Applications of Evolutionary Computation), and a new special track on Evolutionary Machine Learning in a joint event collectively known as EvoStar (Evo*). Accepted papers will be published by Springer Nature in the Lecture Notes in Computer Science series. (See https://link.springer.com/conference/evocop for previous proceedings.) The best regular paper presented at EvoCOP 2022 will be distinguished with a Best Paper Award. EvoCOP conference is now ranked B in the CORE 2021 ranking: http://portal.core.edu.au/conf-ranks/2195/ **** Areas of Interest and Contributions **** EvoCOP welcomes submissions in all experimental and theoretical aspects of evolutionary computation and other metaheuristics to combinatorial optimisation problems, including (but not limited to) the following areas: * Applications of metaheuristics to combinatorial optimisation problems * Theoretical developments * Neighbourhoods and efficient algorithms for searching them * Variation operators for stochastic search methods * Constraint-handling techniques * Parallelisation and grid computing * Search space and landscape analyses * Comparisons between different (also exact) methods * Automatic algorithm configuration and design Prominent examples of metaheuristics include (but are not limited to): * Evolutionary algorithms * Estimation of distribution algorithms * Swarm intelligence methods such as ant colony and particle swarm optimisation * Artificial immune systems * Local search methods such as simulated annealing, tabu search, variable neighbourhood search, iterated local search, scatter search and path relinking * Hybrid methods such as memetic algorithms * Matheuristics (hybrids of exact and heuristic methods) * Hyper-heuristics and autonomous search * Surrogate-model-based methods Notice that, by tradition, continuous/numerical optimisation is *not* part of the topics of interest of EvoCOP. Interested authors might consider submitting to other EvoStar conferences such as EvoApplications. **** Submission Details **** Paper submissions must be original and not published elsewhere. The submissions will be peer reviewed by members of the program committee. The reviewing process will be double-blind, please omit information about the authors in the submitted paper. Submit your manuscript in Springer LNCS format: http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0 Page limit: 16 pages Submission link: coming soon The authors of accepted papers will have to improve their paper on the basis of the reviewers? comments and will be asked to send a camera-ready version of their manuscripts. At least one author of each accepted work has to register for the conference, attend the conference and present the work. **** Important Dates **** Submission deadline: November 1, 2021 EvoStar: April 20-22, 2022 **** EvoCOP Programme Chairs **** Leslie P?rez C?ceres Pontificia Universidad Cat?lica de Valpara?so, Chile leslie.perez at pucv.cl S?bastien Verel Universit? du Littoral C?te d'Opale (ULCO), France verel at univ-littoral.fr -- Leslie P?rez C?ceres Escuela de Ingenier?a Inform?tica Pontificia Universidad Cat?lica de Valpara?so Directora Diplomado en Inteligencia Artificial http://diplomadoia.inf.ucv.cl Co-chair , EvoCOP 2022, April 20-22 http://www.evostar.org/2022/evocop/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From d.bach at ucl.ac.uk Mon Aug 2 02:14:24 2021 From: d.bach at ucl.ac.uk (Dominik R. Bach) Date: Mon, 2 Aug 2021 08:14:24 +0200 Subject: Connectionists: Post doc in cognitive neuroscience/virtual reality research at University College London (movement trajectories, wearable MEG, human behaviour under threat, PI Dominik Bach) Message-ID: <1125ca50-9269-9fb5-7c76-f8296faa41ca@ucl.ac.uk> We are looking for a research fellow in an ERC-funded research project "Action selection under threat - the complex control of human defence" led by Dominik Bach (http://bachlab.org ) at University College London. The position will be based at the Max-Planck UCL Centre for Computational Psychiatry (https://www.mps-ucl-centre.mpg.de/en ). OPM-MEG research takes place at the Wellcome Centre for Human Neuroimaging (http://www.fil.ion.ucl.ac.uk/ ). Our immersive virtual reality lab is based at the UCL Department for Clinical and Movement Neuroscience. These places offer world-class training and networking opportunities and an intellectually vibrant and inspiring research culture. The overarching goal of the project is to understand the computational algorithms of decision-making under acute, immediate threat. We investigate this in an immersive virtual reality (VR) environment, in which people can move to avoid a large number of different threats. The candidate will design and perform human behavioural experiments and analyse movement trajectories. They will also develop and perform MEG experiments using wearable sensors (OPM). The role requires a good understanding of human VR experimentation as well as an interest in using wearable MEG. The interdisciplinary project team is composed of VR experts, psychologists, movement scientists, and decision theorists, and we are looking for an individual who enjoys working in a team environment. Within the topical focus, the project offers freedom to explore and develop novel experimental manipulations that allow inference on the mechanisms of decision-making and action selection. Successful applicants will have an established track record of experimental human research using virtual reality or OPMs, and a strong interest in combining both. They will have a PhD in cognitive-computational (neuro)science, applied machine-learning, motor science, a quantitative field of psychology (e.g. decision-making, perception), or a related area by the agreed start date of the position. They will be keen to solve technical challenges. We are looking for an individual who is strongly motivated to pursue an academic career and is excited by the opportunities for personal and career development this position can provide. The post is available from October 2021 and funded for up to 3 years with initial appointment for 1 year. Starting salary is on UCL grade 7, ranging from ?36,028 to ?43,533 per annum, inclusive of London Allowance, superannuable. More information and access to the UCL online application portal: https://is.gd/sOiFPc Please contact d.bach at ucl.ac.uk for any queries about the project or role. *Closing date: 24 August (tbc)* Interviews will be held remotely in late August/early September. Apologies for cross-posting. -- ----------------------- Dominik R Bach MBBS PhD Principal Research Fellow Max Planck UCL Centre for Computational Psychiatry and Ageing Research Wellcome Centre for Human Neuroimaging, University College London bachlab.org | @bachlab_cog -------------- next part -------------- An HTML attachment was scrubbed... URL: From terry at salk.edu Tue Aug 3 13:21:44 2021 From: terry at salk.edu (Terry Sejnowski) Date: Tue, 03 Aug 2021 10:21:44 -0700 Subject: Connectionists: NEURAL COMPUTATION - August 1, 2021 In-Reply-To: Message-ID: Neural Computation - Volume 33, Number 8 - August 1, 2021 available online for download now: http://www.mitpressjournals.org/toc/neco/33/8 http://cognet.mit.edu/content/neural-computation ----- Letters Simulating and Predicting Dynamical Systems With Spatial Semantic Pointers Aaron R Voelker, Peter Blouw, Xuan Choo, Nicole Sandra-Yaffa Dumont, Terrence C. Stewart, and Chris Eliasmith Frequency Selectivity of Neural Circuits With Heterogeneous Discrete Transmission Delays Akke Mats Houben Learning Brain Dynamics With Coupled Low-dimensional Nonlinear Oscillators and Deep Recurrent Network Germ?n Ezequiel Abrevaya, Guillaume Dumas, Aleksandr Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James Kozloski, Pablo Polosecki, Guillaume Lajoie, David Cox, Silvina Ponce Dawson, Guillermo Cecchi, and Irina Rish Direction Matters: On Influence-Preserving Graph Summarization and Max-cut Principle for Directed Graphs Wenkai Xu, Gang Niu, Aapo Hyvarinen, and Masashi Sugiyama Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting Zeke Xie, Fengxiang He, Shaopeng Fu, Issei Sato, Dacheng Tao, and Masashi Sugiyama Power Function Error Initialization Can Improve Convergence of Backpropagation Learning in Neural Networks for Classification Andreas Knoblauch Storage Capacity of Quaternion-Valued Hopfield Neural Networks With Dual Connections Masaki Kobayashi Randomized Self Organizing Map Nicolas Rougier, Georgios Is. Detorakis Pathological Spectra of the Fisher Information Metric and Its Variants in Deep Neural Networks Ryo Karakida, Shun-ichi Amari, and Shotaro Akaho ----- ON-LINE -- http://www.mitpressjournals.org/neco MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu ----- From aldo.lipani at acm.org Tue Aug 3 15:50:16 2021 From: aldo.lipani at acm.org (Aldo Lipani) Date: Tue, 3 Aug 2021 21:50:16 +0200 Subject: Connectionists: CIKM 2021 - AnalytiCup Challenge In-Reply-To: References: Message-ID: ?* Apologies for cross-posting * ** Announcing CIKM2021 sponsored AnalytiCup challenge ** ************************************************************************************ ** QQ Browser 2021AI Algorithm Competition ** In conjunction with CIKM 2021 (https://cikm2021.org/) (1-5 November 2021) Organized by QQ Browser. Official task page here:?https://algo.browser.qq.com/#en ************************************************************************************ Information feeds has already become an important information resource. Al algorithms are essential for understanding information in multiple modalities. QQ browser, with support from CCF TCMT and top AI conference ACM CIKM, hold the 2021 QQ Browser AI competition. There are two tracks, ?Multimodal Video Similarity? and ?Automated Hyperparameter Optimization?, in this competition. We are looking forward to the great ideas and solutions from industry and academia all around the world. Task 1 Multimodal Video Similarity: This task provides the anonymized features of 1 million short videos from QQ Browser feeds to train the video embedding model. Then, the video pair similarity scores are computed based on the embedding vectors. The predicted scores are evaluated against human-annotated ground truth using Spearman?s rank correlation. Task 2 Automated Hyperparameter Optimization: This track aims at automated hyperparameters optimization based on anonymized realistic industrial tasks and datasets. Given the space of all possible hyperparameters' values, a reward could be achieved with a set of hyperparameters in each iteration. The participants are asked to maximize the reward within a given limit of iterations with a hyperparameters optimization algorithm. Rules of the competition The Competition is open to all individuals?one account per participant. Competition Organizer, Sponsors, and their respective affiliates, subsidiaries, contractors, agents, judges, and advertising and promotion agencies are not eligible to participate in the public competition. If there is one Tencent employee in your team, your team should be identified as an unofficial team and cannot take the reward in the public competition. The score will be counted by the team. One individual can only join one team. A team could have at most 3 members. The leader must undertake joint liability for all actions of the team and members. The deadline for team joining, leaving and team name changing is 2:00 UTC+8, September 20. The winners will be invited for a presentation in CIKM which is one of the top AI international conferences. For the date and submission details of the sharing material, please wait for further notification. Schedule 2021-08-15 12:00:00 (UTC+8): Registration opens 2021-08-15 12:00:00 (UTC+8): Preliminary round submission starts 2021-09-05 12:00:00 (UTC+8): Identity Verification deadline 2021-09-20 12:00:00 (UTC+8): Team joining, leaving and team name changing deadline 2021-09-29 11:59:59 (UTC+8): Preliminary round submission ends 2021-09-30 15:00:00 (UTC+8): Preliminary round Leaderboard final updates. The top 5% of all the teams (no more than 50 teams for each track, subject to organizer alternation) would move on to the final 2021-10-01 12:00:00 (UTC+8): Final round datasets release and submission starts 2021-10-15 11:59:59 (UTC+8): Final round submission ends 2021-10-15 - 2021-10-30 (UTC+8): Challenge award notification, code submission and paper submission 2021-11-01 - 2021- 11- 05 (UTC+10): CIKM conference Awards Track 1 Multimodal Content Understanding 1st place: RMB 200,000 per team 2nd place: RMB 50,000 per team 3rd place: RMB 20,000 per team 4th place: RMB 10,000 per team 5th to 20th places: RMB 3,000 per team Track 2: HPO of recommendation System 1st place: RMB 30,000 per team 2nd place: RMB 15,000 per team 3rd place: RMB 10,000 per team 4th to 20th places: RMB 2,000 per team Dr. Aldo?Lipani?|?aldolipani.com Asst. Prof. in Machine Learning University College London (UCL) -------------- next part -------------- An HTML attachment was scrubbed... URL: From uygars at alleninstitute.org Tue Aug 3 18:53:03 2021 From: uygars at alleninstitute.org (Uygar Sumbul) Date: Tue, 3 Aug 2021 22:53:03 +0000 Subject: Connectionists: Scientist/Postdoc in Computational Neuroscience at Allen Institute Message-ID: POSITION SUMMARY: The mission of the Allen Institute is to unlock the complexities of bioscience and advance our knowledge to improve human health. Using an open science, multi-scale, team-oriented approach, the Allen Institute focuses on accelerating foundational research, developing standards and models, and cultivating new ideas to make a broad, transformational impact on science. The Allen Institute has been a leader in the field of neuroscience for over 17 years; in 2021 we are launching a new research division to understand how dynamic neuronal signals at the level of the entire brain implement fundamental computations and drive flexible behaviors. (https://alleninstitute.org/what-we-do/aix2/) Using a team science approach, we strive to uncover the neural basis of behavior through technological innovation, cutting-edge experiments, modeling, and theory. As part of this initiative, we plan to generate high-throughput images of the complete arbors of individual neurons. Both the size and the complexity of these datasets require an automated approach to the reconstruction of neuronal arbors. We are seeking to fill a position at the level of Scientist to work with the Institute?s quantitative and experimental scientists on high-priority problems in neuronal reconstruction and analysis that include (i) topology-preserving approaches to neuronal segmentation, (ii) deep learning-based analysis of morpho-molecular datasets, and (iii) high performance computing. The Allen Institute believes that team science significantly benefits from the participation of diverse voices, experiences, and backgrounds. Progress in science benefits from multiple perspectives. We are committed to increasing diversity across every team and encourage people from all backgrounds to apply for this role. JOB RESPONSIBILTIES: * Develop novel algorithms to improve the quality of neuron reconstruction in whole-brain images * Analyze the quality of resulting reconstructions * Develop novel methods to improve the overall throughput of a human-in-the-loop pipeline * Participate in a highly interactive and multidisciplinary environment * Publish/present findings in peer-reviewed journals/scientific conferences Note: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This description reflects management?s assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned. BASIC QUALIFICATIONS: * PhD degree in computer science, neuroscience, physics, mathematics, applied mathematics, engineering, or related field, or equivalent combination of degree and experience * Demonstrated proficiency in scientific computing PREFERRED QUALIFICATIONS: * 0-4 years postdoctoral experience * Experience in image segmentation with neural networks * Experience with modern machine learning paradigms such as reinforcement learning and supervised learning * Experience in computational topology * Experience in high-performance computing * Ability to work in a collaborative environment * Proven independent thinking * Experience in computational neuroscience * Strong publication record WORK ENVIRONMENT: * May enter laboratory environment, including potential exposure to lasers, biohazards PHYSICAL DEMANDS: * Fine motor movements in fingers/hands to operate computers and lab equipment POSITION TYPE/EXPECTED HOURS OF WORK * This role is currently able to work remotely due to COVID-19 and our focus on employee safety. We are a Washington State employer, and remote work must be performed in Washington State. We continue to evaluate the safest options for our employees. As restrictions are lifted in relation to COVID-19, this role will return to work onsite. TRAVEL: * Attendance and participation in national and international conferences required ADDITIONAL COMMENTS: * **Please note, this opportunity offers relocation assistance** * **Please note, this opportunity offers work visa sponsorship** It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities. To apply please visit https://alleninstitute.hrmdirect.com/employment/job-opening.php?req=1679008&&cust_sort1=29268&&nohd#job Uygar S?mb?l Assistant Investigator Allen Institute for Brain Science -------------- next part -------------- An HTML attachment was scrubbed... URL: From dftschool at ini.rub.de Tue Aug 3 10:06:41 2021 From: dftschool at ini.rub.de (DFT Summer School) Date: Tue, 3 Aug 2021 16:06:41 +0200 Subject: Connectionists: Neuronal Dynamics for Embodied Cognition - Virtual Summer School 2021. Workshop application deadline closing soon! Message-ID: <1af0ed22-1d1f-f17c-b461-a164f305edc6@ini.rub.de> Please forward this advertisement to whoever you think might be interested. This virtual edition of our summer school will consist of two parts: A live-lecture series and a hands-on workshop. Participation in any part of the school is free of charge. The deadline for workshop applications is Aug 11, 2021! Thanks, Raul Grieben and Jan Tek?lve --- Virtual DFT School 2021 This year our summer school "Neural Dynamics for Embodied Cognition" will take place in virtual form from the 6th to the 11th of September, 2021. Neuronal dynamics provide a powerful theoretical language for the design and modeling of embodied and situated cognitive systems. This school provides a hands-on and practical introduction to neuronal dynamics ideas and enables participants to become productive within this framework. The school is aimed at advanced undergraduate or graduate students, postdocs and faculty members in embodied cognition, cognitive science, and robotics. Topics addressed include neural dynamics, attractor dynamics and instabilities, dynamic field theory, neuronal representations, artificial perception, simple forms of cognition including detection and selection decisions, memory formation, learning, and grounding relational concepts. This virtual edition of our summer school will consist of two parts: A live-lecture series and a hands-on workshop. The lecture series will be held as a video conference and provides a step-by-step introduction to Dynamic Field Theory. The two-and-a-half-day project workshop gives students the opportunity to put to use the newly acquired skills in a concrete hands-on modeling project. Students solve the task in our open-source simulation environment under the guidance of a personal tutor. This year's lectures will be open for everyone,? while the one-on-one tutoring limits the number of participants who can take part in the workshop. We also encourage workshop applications by small groups of participants, maybe two or three colleagues who will work together locally on the same project and may share a tutor. Although this format will not retain the appeal of meeting other students in person, we will make this year's experience as interactive as possible. The lecture series will be held from the 6th to the 11th of September and the workshop takes place from the 9th to the 11th of September. Lectures will take place from 3 to 6 p.m. (CET) on each day and personal tutoring will be available on each workshop day. Participation in any part of the school is free of charge. To apply for the lecture series and/or the workshop, please visit our webpage: https://dynamicfieldtheory.org/events/summer_school_2021/ From laurenz.wiskott at rub.de Mon Aug 2 08:32:38 2021 From: laurenz.wiskott at rub.de (Laurenz Wiskott) Date: Mon, 2 Aug 2021 14:32:38 +0200 Subject: Connectionists: PhD position with Prof. Laurenz Wiskott at the Institute for Neural Computation, Bochum, Germany Message-ID: <20210802123238.GB3362@curry> The Ruhr-Universit?t Bochum is one of the leading research universities. The university draws its strengths from both the diversity and the proximity of scientific and engineering disciplines on a single, coherent campus. This highly dynamic setting enables students and researchers to work across traditional boundaries of academic subjects and faculties. One particular strength of RUB is interdisciplinary research in Machine Learning and Artificial Intelligence, see https://ml-ai.rub.de/. The Institute for Neural Computation is a central research institute, see https://www.ini.rub.de/. It focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. There is an open position for a research assistant / Phd-student in the group ?Theory of Neural Systems? of Prof. Dr. Laurenz Wiskott to be filled at 15th of Septembert. The appointment will be for three years. Salary is 75% of salary scale TV-L E13. Task: ? Develop a generative model for learning high-level representations of images that ideally should include visual invariances, should enable attention driven selection, and support classification of objects. A promising basis for the development is the vector quantizes variational autoencoder (VQ-VAE). The system will be developed with methods from machine learning but should integrate well into a system-level model of episodic memory. ? Present results on conferences and publish them in journals of machine learning or computational neuroscience. ? Teaching assistance for 3 semester hours per week. ? Constructive contributions to the research group. We offer: ? An interesting interdisciplinary environment in the field of Machine Learning / Artificial Intelligence / Computational Neuroscience. ? Room to develop your own ideas in the project. ? Infrastructure to integrate well into the institute and the group. ? Opportunity to do a PhD (Dr). Applications (CV, transcript of records for MSc and BSc, statement of purpose) should be sent as a single pdf file to laurenz.wiskott at rub.de. Travel expenses for interviews will not be refunded. Ruhr-University Bochum is committed to equal opportunity in employment and gender equality in its working environment. We therefore look forward to applications from qualified women. Applications from appropriately qualified handicapped persons are also encouraged. Requirements: ? Very good Master in mathematics, computer science, engineering, or a related field. ? Good programming and mathematical skills. ? Interest in interdisciplinary research questions and cooperations. Advantageous: ? Experience in Machine Learning and/or Computational Neuroscience. ? Good communication and teamwork skills. ? Experience in interdisciplinary projects. ? Programming skills in Python. From dayan at tue.mpg.de Wed Aug 4 00:34:55 2021 From: dayan at tue.mpg.de (Peter Dayan) Date: Wed, 4 Aug 2021 06:34:55 +0200 Subject: Connectionists: =?utf-8?q?Seeking_Scientific_Software_Engineer_?= =?utf-8?b?QCBUw7xiaW5nZW4=?= Message-ID: <20210804043455.l666cojn4uvqcjo3@tuebingen.mpg.de> My lab at the Max Planck Institute for Biological Cybernetics in T?bingen, Germany, is looking to hire a Scientific Software Engineer. We build and test theories and computational models of neural processing, with a particular emphasis on decision-making, learning and representation. We are therefore looking for someone with excellent skills and experience in programming and data analysis to help us develop, test and implement scientific software across our interdisciplinary projects. Full details at: https://www.kyb.tuebingen.mpg.de/577071/scientific-software-engineer1?c=70261 Preference will be given to applications received by September 10th, 2021. The Max Planck Society endeavours to employ more severely handicapped people. Applications of severely disabled persons are expressly desired. The Max Planck Society strives for gender and diversity equality. We welcome applications from people from all backgrounds. -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/x-pkcs7-signature Size: 4936 bytes Desc: not available URL: From timofte.radu at gmail.com Tue Aug 3 06:40:39 2021 From: timofte.radu at gmail.com (Radu Timofte) Date: Tue, 3 Aug 2021 12:40:39 +0200 Subject: Connectionists: Last CfP: ICCV 2021 Advances in Image Manipulation workshop [DEADLINE Aug. 05] Message-ID: Apologies for cross-posting ******************************* CALL FOR PAPERS AIM: 3rd Advances in Image Manipulation workshop 2021 In conjunction with ICCV 2021, October 16, Montreal, Canada (VIRTUAL) Website: https://data.vision.ee.ethz.ch/cvl/aim21/ Contact: radu.timofte at vision.ee.ethz.ch TOPICS Papers addressing topics related to image/video manipulation, restoration and enhancement are invited. The topics include, but are not limited to: ? Image-to-image translation ? Video-to-video translation ? Image/video manipulation ? Perceptual manipulation ? Image/video generation and hallucination ? Image/video quality assessment ? Image/video semantic segmentation ? Perceptual enhancement ? Multimodal translation ? Depth estimation ? Image/video inpainting ? Image/video deblurring ? Image/video denoising ? Image/video upsampling and super-resolution ? Image/video filtering ? Image/video de-hazing, de-raining, de-snowing, etc. ? Demosaicing ? Image/video compression ? Removal of artifacts, shadows, glare and reflections, etc. ? Image/video enhancement: brightening, color adjustment, sharpening, etc. ? Style transfer ? Hyperspectral imaging ? Underwater imaging ? Aerial and satellite imaging ? Methods robust to changing weather conditions / adverse outdoor conditions ? Image/video manipulation on mobile devices ? Image/video restoration and enhancement on mobile devices ? Studies and applications of the above. SUBMISSION A paper submission has to be in English, in pdf format, and at most 8 pages (excluding references) in ICCV style. The paper format must follow the same guidelines as for all ICCV submissions. http://iccv2021.thecvf.com/node/4 The review process is double blind. Authors do not know the names of the chair/reviewers of their papers. Reviewers do not know the names of the authors. Dual submission is allowed with ICCV main conference only. If a paper is submitted also to ICCV and accepted, the paper cannot be published both at the ICCV and the workshop. For the paper submissions, please go to the online submission site https://cmt3.research.microsoft.com/AIMICCV2021 Accepted and presented papers will be published after the conference in the ICCV Workshops Proceedings. The author kit provides a LaTeX2e template for paper submissions. Please refer to the example for detailed formatting instructions. If you use a different document processing system then see the ICCV author instruction page. Author Kit: http://iccv2021.thecvf.com/sites/default/files/2020-09/iccv2021AuthorKit.zip WORKSHOP DATES ? Submission Deadline: August 05, 2021 ? Decisions: August 12, 2021 ? Camera Ready Deadline: August 16, 2021 ORGANIZERS ? Radu Timofte (ETH Zurich, Switzerland and University of W?rzburg, Germany) ? Andrey Ignatov, Kai Zhang, Dario Fuoli, Andres Romero, Martin Danelljan (ETH Zurich, Switzerland) ? Luc Van Gool (KU Leuven, Belgium and ETH Zurich, Switzerland) ? Ming-Hsuan Yang (University of California at Merced and Google, US ? Kyoung Mu Lee (Seoul National University, Korea) ? Eli Shechtman (Adobe Research, US) ? Ming-Yu Liu (Nvidia, US) ? Egor Ershov (IITP RAS, Russia) ? Marko Subasic (University of Zagreb, Croatia) ? Michael S. Brown (York University, Canada) SPEAKERS (TBA) SPONSORS (TBA) CONTACT Email: radu.timofte at vision.ee.ethz.ch Website: https://data.vision.ee.ethz.ch/cvl/aim21/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From mohsen.jafarzade at gmail.com Sun Aug 1 14:03:26 2021 From: mohsen.jafarzade at gmail.com (Mohsen Jafarzadeh) Date: Sun, 1 Aug 2021 12:03:26 -0600 Subject: Connectionists: [jobs] Several post-doctoral (senior research assistant) and research associate positions at UCCS Message-ID: Several post-doctoral (senior research assistant) and research associate positions at UCCS Dr. Terrance Boult and his team at the El Pomar Institute for Innovation and Commericalization (EPIIC) at the University of Colorado Colorado Springs (UCCS) are seeking one or more highly motivated advanced post-doctoral researcher(s) and research associate with a strong record of accomplishment in machine learning and computer vision, ideally with incremental learning, deep learning, or open-set learning, and/or with biometrics and computational photography. You will be expected to work closely with Dr. Boult and his graduate/undergraduate students on: - formalized models for open world learning with extreme-value theory - semi-supervised and unsupervised incremental learning - open world learning for object classification and detection - open world learning in visual observation of games - long-range imaging, de-blurring, and face recognition Deadline for applications is August 29, 2021. The potential employee start date is September 15, 2021. Apply via the following link: https://cu.taleo.net/careersection/targeted+hire/jobdetail.ftl?job=22201&lang=en Contact Name: Terrance Boult Contact Email: tboult at vast.uccs.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From franrruiz87 at gmail.com Wed Aug 4 16:09:56 2021 From: franrruiz87 at gmail.com (=?UTF-8?Q?Francisco_J=2E_Rodr=C3=ADguez_Ruiz?=) Date: Wed, 4 Aug 2021 22:09:56 +0200 Subject: Connectionists: =?utf-8?b?W0NmUF0gSSAoU3RpbGwpIENhbuKAmXQgQmVs?= =?utf-8?q?ieve_It=E2=80=99s_Not_Better!_ICBINB=40NeurIPS_Workshop?= Message-ID: *Call for Papers: I (Still) Can?t Believe It?s Not Better!A workshop for ?beautiful? ideas that should have worked* *Workshop date:* 13th or 14th December 2021 *Location:* Virtual, at NeurIPS 2021 *Website:* https://i-cant-believe-its-not-better.github.io/neurips2021/ *Submission deadline:* September 17th 2021 Beautiful ideas have shaped scientific progress throughout history. However, beautiful ideas are often overlooked in a research environment that heavily emphasizes state-of-the-art (SOTA) results, where the worth of scientific works is defined by their immediate utility. We invite submissions to ?I (Still) Can?t Believe It?s Not Better!? (ICBINB) Workshop @ NeurIPS2021. ICBINB will explore gaps between the ?form? and ?function? of ideas in ML and AI research. Do you have a beautiful (?form?) idea which does not yet work (?function?)? We welcome the submission of research papers and abstracts from the broader ML community describing original work that has not been submitted or currently under review, has not been previously published nor accepted for publication elsewhere, in any other journal or conference. In particular, this work may touch on one or more of the following aspects: + Unexpected negative results or anomalies: ideas that do not provide expected results, yet authors are able to explain why, bringing an interesting closed-form piece of knowledge to the community. + Papers that are ?stuck? yet contain beautiful/elegant ideas. Authors should argue why the idea is of interest, rigorously describe the analysis, and include a self-critique. + Criticism of and alternatives to default or standard practices (e.g., current evaluation metrics). + Meta-research on the role of ?beauty? or negative results in broader ML research (including statistics, data science, AI, and application areas). Submissions should be 4 pages long at most (not including references) and submitted via OpenReview platform by September 17th 2021 (see our website for the submission link). The Appendix can be unlimited, but note that reviewers are only required to read the main text. Accepted authors will be invited to participate in a poster session at the workshop. These submissions are non-archival, however reviewers will nominate exemplar papers for submission in PMLR. This workshop evolves from last year ICBINB at NeurIPS 2020 workshop. This year, we expand the scope to a broader ML community beyond probabilistic ML, and will further unpack the concept of beauty of ideas during the workshop. *Confirmed invited speakers*: Tom Griffiths (Princeton University, USA), Michaela Rosca (DeepMind, London), Robert Williamson (T?bingen University, Germany), Cosma Shalizi (Carnegie Mellon University, USA), Tina Eliassi-Rad (Northeastern University, USA). -- Francisco J. R. Ruiz Research Scientist DeepMind -------------- next part -------------- An HTML attachment was scrubbed... URL: From hocine.cherifi at gmail.com Wed Aug 4 04:21:54 2021 From: hocine.cherifi at gmail.com (Hocine Cherifi) Date: Wed, 4 Aug 2021 10:21:54 +0200 Subject: Connectionists: CFP COMPLEX NETWORKS 2021, 10th International Conference on Complex Networks & Applications, Nov.30- Dec. O2, 2021 | Hybrid | Submission deadline: 01 Sep 2021 Message-ID: *10th** International Conference on Complex Networks & Their Applications* Madrid, Spain (online & in-person) -* November 30 - December 02, 2021* COMPLEX NETWORKS 2021 You are cordially invited to submit your contribution until September 01, 2021. *SPEAKERS * ? Marc Barth?l?my CEA France ? Ginestra Bianconi Queen Mary University of London UK ? Jo?o Gama University of Porto Portugal ? Dirk Helbing ETH Z?rich Switzerland ? Yizhou Sun UCLA USA ? Alessandro Vespignani Northeastern University USA *TUTORIALS (November 29, 2021)* ? Elisabeth Lex Graz University of Technology Austria ? Giovanni Petri ISI Foundation Italy *PUBLICATION* Full papers (not previously published up to 12 pages) and Extended Abstracts (about published or unpublished research up to 3 pages) are welcome. ? *Papers *will be included in the conference *proceedings edited by Springer* ? *Extended abstracts* will be published in the *Book of Abstracts (with ISBN)* Templates are available on the submission webpage. If in doubt, please contact the Publication Chair (matteo.zignani at unimi.it) All contributions should be submitted via EasyChair . Extended versions will be invited for publication in *special issues of international journals:* o Applied Network Science edited by Springer o Complex Systems o Computational Social Networks edited by Springer o Network Science edited by Cambridge University Press o PLOS one o Social Network Analysis and Mining edited by Springer *TOPICS* *Topics include, but are not limited to: * o Models of Complex Networks o Structural Network Properties and Analysis o Complex Networks and Epidemics o Community Structure in Networks o Community Discovery in Complex Networks o Motif Discovery in Complex Networks o Network Mining o Network embedding methods o Machine learning with graphs o Dynamics and Evolution Patterns of Complex Networks o Link Prediction o Multilayer Networks o Network Controllability o Synchronization in Networks o Visual Representation of Complex Networks o Large-scale Graph Analytics o Social Reputation, Influence, and Trust o Information Spreading in Social Media o Rumour and Viral Marketing in Social Networks o Recommendation Systems and Complex Networks o Financial and Economic Networks o Complex Networks and Mobility o Biological and Technological Networks o Mobile call Networks o Bioinformatics and Earth Sciences Applications o Resilience and Robustness of Complex Networks o Complex Networks for Physical Infrastructures o Complex Networks, Smart Cities and Smart Grids o Political networks o Supply chain networks o Complex networks and information systems o Complex networks and CPS/IoT o Graph signal processing o Cognitive Network Science o Network Medicine o Network Neuroscience o Quantifying success through network analysis o Temporal and spatial networks o Historical Networks Join us at COMPLEX NETWORKS 2021 Madrid Spain *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comt? Deputy Director LIB EA N? 7534 Editor in Chief Applied Network Science Editorial Board member PLOS One , IEEE ACCESS , Scientific Reports , Journal of Imaging , Quality and Quantity , Computational Social Networks , Complex Systems Complexity -------------- next part -------------- An HTML attachment was scrubbed... URL: From dwang at cse.ohio-state.edu Tue Aug 3 10:51:02 2021 From: dwang at cse.ohio-state.edu (Wang, Deliang) Date: Tue, 3 Aug 2021 14:51:02 +0000 Subject: Connectionists: NEURAL NETWORKS, Aug. 2021 Message-ID: Neural Networks - Volume 140, August 2021 https://www.journals.elsevier.com/neural-networks Basic theorem and global exponential stability of differential-algebraic neural networks with delay Jiejie Chen, Boshan Chen, Zhigang Zeng SPLASH: Learnable activation functions for improving accuracy and adversarial robustness Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi TigeCMN: On exploration of temporal interaction graph embedding via Coupled Memory Neural Networks Zhen Zhang, Jiajun Bu, Zhao Li, Chengwei Yao, ... Jia Wu Exploring the spatial reasoning ability of neural models in human IQ tests Hyunjae Kim, Yookyung Koh, Jinheon Baek, Jaewoo Kang Long-term Cognitive Network-based architecture for multi-label classification Gonzalo Napoles, Marilyn Bello, Yamisleydi Salgueiro Empirical strategy for stretching probability distribution in neural-network-based regression Eunho Koo, Hyungjun Kim Improved deep CNNs based on Nonlinear Hybrid Attention Module for image classification Nan Guo, Ke Gu, Junfei Qiao, Jing Bi Parallel orthogonal deep neural network Peyman Sheikholharam Mashhadi, S?awomir Nowaczyk, Sepideh Pashami Dual self-paced multi-view clustering Zongmo Huang, Yazhou Ren, Xiaorong Pu, Lili Pan, ... Guoxian Yu Diversity-driven knowledge distillation for financial trading using Deep Reinforcement Learning Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas Bidirectional stochastic configuration network for regression problems Weipeng Cao, Zhongwu Xie, Jianqiang Li, Zhiwu Xu, ... Xizhao Wang A clustering-based adaptive Neighborhood Retrieval Visualizer Dominik Olszewski PyDiNet: Pyramid Dilated Network for medical image segmentation Mourad Gridach Manifold adversarial training for supervised and semi-supervised learning Shufei Zhang, Kaizhu Huang, Jianke Zhu, Yang Liu Self-organized Operational Neural Networks with Generative Neurons Serkan Kiranyaz, Junaid Malik, Habib Ben Abdallah, Turker Ince, ... Moncef Gabbouj Learning dual-margin model for visual tracking Nana Fan, Xin Li, Zikun Zhou, Qiao Liu, Zhenyu He On decision regions of narrow deep neural networks Hans-Peter Beise, Steve Dias Da Cruz, Udo Schroeder Understanding the message passing in graph neural networks via power iteration clustering Xue Li, Yuanzhi Cheng A statistical framework for non-negative matrix factorization based on generalized dual divergence Karthik Devarajan Multistability of delayed fractional-order competitive neural networks Fanghai Zhang, Tingwen Huang, Qiujie Wu, Zhigang Zeng LSTM-based approach for predicting periodic motions of an impacting system via transient dynamics Kenneth Omokhagbo Afebu, Yang Liu, Evangelos Papatheou, Bingyong Guo Speaker recognition based on deep learning: An overview Zhongxin Bai, Xiao-Lei Zhang Smoothing inertial neurodynamic approach for sparse signal reconstruction via -norm minimization You Zhao, Xiaofeng Liao, Xing He, Rongqiang Tang, Weiwei Deng Speaker separation in realistic noise environments with applications to a cognitively-controlled hearing aid Bengt J. Borgstrom, Michael S. Brandstein, Gregory A. Ciccarelli, Thomas F. Quatieri, Christopher J. Smalt Uncorrelated feature encoding for faster image style transfer Minseong Kim, Hyun-Chul Choi Tumor attention networks: Better feature selection, better tumor segmentation Shuchao Pang, Anan Du, Mehmet A. Orgun, Yunyun Wang, Zhenmei Yu Cycle consistent network for end-to-end style transfer TTS training Liumeng Xue, Shifeng Pan, Lei He, Lei Xie, Frank K. Soong Multi-resolution modulation-filtered cochleagram feature for LSTM-based dimensional emotion recognition from speech Zhichao Peng, Jianwu Dang, Masashi Unoki, Masato Akagi -------------- next part -------------- An HTML attachment was scrubbed... URL: From Francesco.Rea at iit.it Thu Aug 5 03:56:51 2021 From: Francesco.Rea at iit.it (Francesco Rea) Date: Thu, 5 Aug 2021 07:56:51 +0000 Subject: Connectionists: [jobs] deadline postponed: Post-doc Functional Memory Network in collaborative AI for cognitive assessment of human partners @ Italian Institute of Technology (IIT) Message-ID: Post-doc Functional Memory Network in collaborative AI for cognitive assessment of human partners At IIT we work enthusiastically to develop human-centered Science and Technology to tackle some of the most pressing societal challenges of our times and transfer these technologies to the production system and society. Our Genoa headquarter is strictly inter-connected with our 11 centers around Italy and two outer-stations based in the US for a truly interdisciplinary experience. The CONTACT Research Line is coordinated by Alessandra Sciutti, who has extensive experience in Cognitive Architecture for Human Robot Interaction. Within the team, your main responsibilities will be: * Sensing of human cognitive capabilities based on human-robot collaboration in unstructured real-world contexts * Design of control systems for mobile robots that enable natural human-robot collaboration * Development of an AI solution for the assessing of cognitive capabilities of human partners in human-robot social collaboration for unstructured real-world scenario This open position is financed by European Commission through HBP (Human Brain Project) project CEoI for SGA3 - Application of functional architectures supporting advanced cognitive functions to address AI and automation problems of industrial and commercial within the PROMEN-AID, Proactive Memory iN AI for Development project (GA 945539). Please submit your application using the online form (https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=it&job=2100004X) and including a detailed CV, cover letter (outlining motivation, experience and qualifications), names and contact of 2 referees. Application's deadline postponed to August 31, 2021. -------------- next part -------------- An HTML attachment was scrubbed... URL: From ioannakoroni at csd.auth.gr Thu Aug 5 04:35:24 2021 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Thu, 5 Aug 2021 11:35:24 +0300 Subject: Connectionists: Invitation to join 2021 Summer Short Course 'Deep Learning and Computer Vision', 23-24th August 2021 References: <048501d778ba$141b69b0$3c523d10$@csd.auth.gr> <001701d778c9$0fecdd60$2fc69820$@csd.auth.gr> Message-ID: <00cc01d789d4$d6798840$836c98c0$@csd.auth.gr> Dear Machine Learning and Deep Neural Networks engineers, scientists and enthusiasts, you are welcomed to register in the CVML Short e-course on 'Deep Learning and Computer Vision', 23-24th August 2021: http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-vi sion-for-autonomous-systems-2021/ It will take place as a two-day e-course (due to COVID-19 circumstances), hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece, providing a series of live lectures delivered through a tele-education platform (Zoom). They will be complemented with on-line video recorded lectures and lecture pdfs, to facilitate international participants having time difference issues and to enable you to study at own pace. You can also self-assess your knowledge, by filling appropriate questionnaires (one per lecture). You will be provided programming to improve your programming skills. You will also have accesses to tutorial exercises to better your theoretical understanding of selected CVML topics. This 6th edition of this course is part of the very successful CVML short course series that took place in the last four years. Course description 'Deep Learning and Computer Vision' The short e-course consists of 16 1-hour live lectures organized in two Parts (1 Part per day): Part A lectures (8 hours) provide an in-depth presentation to autonomous systems imaging and the relevant architectures as well as a solid background on the necessary topics of computer vision (Image acquisition, camera geometry, Stereo and Multiview imaging, Mapping and Localization) and machine learning (Introduction to neural networks, Perceptron, backpropagation, Deep neural networks, Convolutional NNs). Part B lectures (8 hours) provide in-depth views of the various topics encountered in autonomous systems perception, ranging from vehicle localization and mapping, to Neural SLAM, target detection and tracking. Part B also contains application-oriented lectures on autonomous drones, cars and marine vessels, e.g., drone mission planning for cinematography and related applications (marine surveillance, infrastructure/building inspection, car vision). Course lectures Part A: (first day, 8 lectures) 1. Introduction to autonomous systems imaging 2. Digital Image and Videos 3. Camera geometry 4. Stereo and Multiview imaging 5. Introduction to Artificial Neural Networks. Perceptron 6. Multilayer perceptron. Backpropagation 7. Deep neural networks. Convolutional NNs 8. Introduction to multiple drone imaging Part B: (second day, 8 lectures) 1. Simultaneous Localization and Mapping 2. Neural Slam 3. Deep Object Detection 4. 2D Visual Object Tracking 5. Drone mission planning and control 6. Introduction to car vision 7. Introduction to autonomous marine vehicles 8. CVML Software Development Tools Though independent, the attendees of this short e-course will greatly benefit by attending the CVML Short e-course on 'Computer Vision for Autonomous Systems' 25-27th August 2021: http://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-deep -learning-and-computer-vision-for-autonomous-systems-2021/ You can use the following link for course registration: http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-vi sion-for-autonomous-systems-2021/ Lecture topics, sample lecture ppts and videos, self-assessment questionnaires, programming exercises and tutorial exercises can be found therein. For questions, please contact: Ioanna Koroni > The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow and IEEE distinguished speaker. He is the coordinator of the EC funded International AI Doctoral Academy (AIDA ), that is co-sponsored by all 5 European AI R&D flagship projects (H2020 ICT48). He was initiator and first Chair of the IEEE SPS Autonomous Systems Initiative. He is Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece. He was Coordinator of the European Horizon2020 R&D project Multidrone. He is ranked 249-top Computer Science and Electronics scientist internationally by Guide2research (2018). He has 33800+ citations to his work and h-index 86+. AUTH is ranked 153/182 internationally in Computer Science/Engineering, respectively, in USNews ranking. Relevant links: 1) Prof. I. Pitas: https://scholar.google.gr/citations?user=lWmGADwAAAAJ &hl=el 2) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/ 3) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/ 4) International AI Doctoral Academy (AIDA): http://www.i-aida.org/ 5) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/ 6) AIIA Lab: https://aiia.csd.auth.gr/ Sincerely yours Prof. I. Pitas Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab) Aristotle University of Thessaloniki, Greece Post scriptum: To stay current on CVML matters, you may want to register in the CVML email list, following instructions in: https://lists.auth.gr/sympa/info/cvml -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus -------------- next part -------------- An HTML attachment was scrubbed... URL: From Francesco.Rea at iit.it Thu Aug 5 03:57:13 2021 From: Francesco.Rea at iit.it (Francesco Rea) Date: Thu, 5 Aug 2021 07:57:13 +0000 Subject: Connectionists: [jobs] deadline postponed: Post-doc Functional Memory Network in collaborative AI for context awareness and action planning in robotics @ Italian Institute of Technology (IIT) Message-ID: <345fd320411648d59c031a0338cc4bc5@iit.it> Post-doc Functional Memory Network in collaborative AI for context awareness and action planning in robotics At IIT we work enthusiastically to develop human-centered Science and Technology to tackle some of the most pressing societal challenges of our times and transfer these technologies to the production system and society. Our Genoa headquarter is strictly inter-connected with our 11 centers around Italy and two outer-stations based in the US for a truly interdisciplinary experience. The CONTACT Research Line is coordinated by Alessandra Sciutti, who has extensive experience in Cognitive Architecture for Human Robot Interaction. Within the team, your main responsibilities will be: * Exploiting functional memory networks and related AI in a cognitive architecture for better human robot collaboration; * Design of control systems for dextrose mobile robots aiming at natural human-robot collaboration; * Development of an AI solution for context awareness in collaborative unstructured manufacturing contexts; * Development of an AI solution for action planning in collaborative unstructured manufacturing contexts. This open position is financed by European Commission through HBP (Human Brain Project) project CEoI for SGA3 - Application of functional architectures supporting advanced cognitive functions to address AI and automation problems of industrial and commercial within the awarded PROMEN-AID, Proactive Memory iN AI for Development project (GA-94553) Please submit your application using the online form (https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=it&job=2100004W) and including a detailed CV, cover letter (outlining motivation, experience and qualifications), names and contact of 2 referees. Application's deadline postponed to August 31, 2021. -------------- next part -------------- An HTML attachment was scrubbed... URL: From tiako at ieee.org Thu Aug 5 15:01:04 2021 From: tiako at ieee.org (Pierre F. Tiako) Date: Thu, 5 Aug 2021 14:01:04 -0500 Subject: Connectionists: (CFP) 2021 OkIP Intl Conf on Automated & Intelligent Systems|| Oklahoma City, USA|| Nov 15-18, 2021 Message-ID: [Apologies if you receive multiple copies, --- Call for Abstracts and Papers ------------- 2021 OkIP International Conference on Automated and Intelligent Systems (CAIS) MNTC Conference Center, Oklahoma City, OK, USA & Online November 15-18, 2021 https://eventutor.com/e/CAIS001 Oklahoma International Publishing (OkIP) is pleased to host the 1st International Conference on Automated and Intelligent Systems (CAIS). The conference aims to bring together scholars from different disciplinary backgrounds to emphasize the dissemination of ongoing research and development in the field. Proposals are solicited describing original works in fields below and related technologies. CAIS will include a peer-reviewed program of technical, industrial, and poster sessions. Accepted and presented full papers from the tracks below will be published by OkIP and submitted for indexation in major abstract and citation databases of peer-reviewed literature. Extended versions of best papers will be considered for the inaugural issue of the International Journal of Information Technology Research ISSN 1553-653X. >> Agent-based, Automated, and Distributed Supports - Multi-Agent Systems - Software Agents - Decentralized Intelligence - Distributed Intelligence - Context-Aware Computing - Group Decision Support Systems - Intelligent Structures - Intelligent Networks - Design Approaches - Automation Approaches - Sensor Networks Architectures - Path Planning - Complex Manufacturing Processes - Analytical Models - Multistage Assembly Line - Automated Inspection >> Intelligent Systems and Applications - Medical Nanorobotics - Sensory Systems - Embedded Systems - Microsatellite - Embedded Systems - Digital Manufacturing - Optimization Algorithms - Evolutionary Algorithms - Bioinformatics Applications - Biotechnology Applications - Computer Vision Applications - Sensor Networks Applications - Intelligent Design - Soft Computing - Ubiquitous Computing - Pervasive Computing - Wearable Computing - Fuzzy Systems - Intelligence Manufacturing - Cyber-physical Systems - Kinematics >> Knowledge-based and Control Supports - Expert Systems - Decision Support Systems - Intelligent Control Systems - Intelligent Supervision Systems - Knowledge Engineering - Complex Systems - Neural Networks - Structural Optimization - Intelligent Teleoperation - Intelligent Shopfloor - Collision Avoidance - Object Detection and Tracking - Path Planning - Position Control - Fault Diagnosis - Quality Control - Motion Control - Preventive Maintenance - Defect Detection - Predictive Control >> Robotics and Vehicles - Unmanned Vehicles - Unmanned Robots - Autonomous Vehicles - Autonomous Robots - Human-Robot Interfaces - Human-Robot Interactions - Robotic Applications - Intelligent Telrobotics - Service Robots - Robotic Manipulators - Self-driving Vehicles - Cloud-based Driving - Robotic Arms - Vehicular ad hoc Networks - Traffic Detection - Vehicle-to-Vehicle Communication - Vehicle Platooning - Steering Systems - Vehicle dynamics - Traffic Computing >> Technical Research & Industry Contribution - Full Paper: Accomplished research results (6 pages) - Short Paper: Work in progress/fresh developments (3 pages) - Poster/Journal First: Displayed/Oral presented (1 page) >> Corporate Showcase & Exhibition - Booth: Display product and/or service offerings (1 page) - Oral: Present product and/or service offerings (1 page) >> Student Poster & Career Fair - Graduate & Doctoral: Peer-reviewed Poster (1 page) - Undergraduate/High School: Selected Poster (1 page) - Recruiter Booth: Product/Service & Job offerings (1 page) >> Workshop, Tutorial, Forum & Panel - Workshop, Tutorial & Tour: Proposal (1 page) - Executive Forum, Panel & Talk: Proposal (1 page) >> Important Dates: - Submission: Aug 31, 2021 - Notification: Sep 26, 2021 - Conference: Nov 15-18, 2021 >> Technical Program Committee https://eventutor.com/event/6/page/12-committee >> Venue https://eventutor.com/event/4/page/9-venue >> Co-located Conferences and Events https://eventutor.com/event/4/page/4-conferences >> For more information, submission details, and important dates, visit: https://eventutor.com/e/CAIS001 Please feel free to contact us for any inquiry at: info at okipublishing.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From torcini at gmail.com Thu Aug 5 12:22:23 2021 From: torcini at gmail.com (A. Torcini) Date: Thu, 5 Aug 2021 18:22:23 +0200 Subject: Connectionists: Workshop "Emergent collective dynamics in neural systems" - DynamicsDays2021 XL Message-ID: Workshop "Emergent collective dynamics in neural systems" Hybrid Mini-Symposium during Dynamics Days 2021 XL - 26-27 August 2021 - Online and in situ at Nice University https://dynamicsdays2021.univ-cotedazur.fr/ The workshop explores recent advancement related to the emergence of coherent dynamics in neural networks, with a focus on a new generation of neural mass models for balanced networks based on developments of the Ott-Antonsen Ansatz for phase oscillator networks. Invited Speakers: Part 1 MS27 11.00-13.00 -- 26/8/2021 S. Coombes, M. di Volo, D. Goldobin, M. Helias Part 2 MS35 11.00-13.00 -- 27/8/2021 H. Taher, V. Hakim, E. Ullner, D. Hansel Organisers; Alessandro Torcini (CY Cergy Paris University) and Antonio Politi (Aberdeen University). Detailed program here : https://dynamicsdays2021.univ-cotedazur.fr/assets/DDays-2021_july26.pdf From constantin.rothkopf at cogsci.tu-darmstadt.de Fri Aug 6 04:15:36 2021 From: constantin.rothkopf at cogsci.tu-darmstadt.de (Constantin Rothkopf) Date: Fri, 6 Aug 2021 10:15:36 +0200 Subject: Connectionists: =?utf-8?b?4oCeQnJpZGdpbmcgZ3JhbnTigJ0gZnJvbSB0?= =?utf-8?q?he_German_Society_for_Cognitive_Science_=28GK=29_for_Bachelor?= =?utf-8?q?=2C_Master_and_PhD_students?= Message-ID: ?Bridging grant? from the German Society for Cognitive Science (GK) for Bachelor, Master and PhD students The German Society for Cognitive Science (GK) would like to support students who find themselves in a difficult (emergency) situation caused by the Corona pandemic with a bridging grant. The grant consists of funding for a maximum of three months ? 500 ? per month. The GK is able to offer six to eight grants. The grant is meant as financial support allowing to finish the respective degree (Bachelor or Master) or providing some financial relief during an important PhD thesis phase (e.g. finishing a paper). The selection will be done by the members of the steering committee of the German Society for Cognitive Science (GK). The committee will consider all emergency cases as long as they have been caused by the Corona pandemic within the context of the studies and/or doctoral programme and are sufficiently substantiated with proof. Target group: The funding is intended for students who are enrolled and/or registered in a German university. In particular, only the following persons are eligible for funding: (1) Bachelor or Master students in subjects belonging to Cognitive Science (e.g. Cognitive Science, Philosophy, Psychology, CS, AI, Linguistics, Neuroscience) who, ideally, will be able to graduate soon, and (2) PhD students registered in one of the subjects belonging to Cognitive Science who are working on a cognitive science project. Persons who already received a bridging grant from the GK are not eligible to apply. Paradigmatic cases: A student pursuing a Master degree has fallen behind with their master thesis because due to the Corona-pandemic there was no constant childcare. The funding could be used to pay for a privately organised childcare. Or a PhD student could not finish his or her dissertation because data acquisition was delayed due to reduced lab capacities. The funding could be used to cover living expenses after the contract has expired. Application and Proof: Please submit: - a statement comprehensibly describing applicant?s situation (cases with evidence are preferred) and indicating the use of the funding. - Bachelor and Master students: -- Enrollment confirmation and transcript of record -- A letter from the faculty?s/program?s advisor confirming the regular continuation of studies, anticipated graduation (within the winter term 2021/2022) - PhD students: -- A short statement from the first supervisor roughly sketching the cognitive science related project and describing the project?s progress. The application shall be emailed with the subject ?Application Bridging Grant? to the following email: Chair of the GK, Prof. Dr. Barbara Kaup, barbara.kaup at uni-tuebingen.de; Application deadline: 15.10.2021 -- Prof. Constantin A. Rothkopf, PhD http://www.cogsci.tu-darmstadt.de/ http://www.pip.tu-darmstadt.de/ https://hessian.ai/ https://fias.uni-frankfurt.de/~rothkopf/ From jasper.bischofberger at posteo.de Thu Aug 5 11:25:35 2021 From: jasper.bischofberger at posteo.de (Jasper Bischofberger) Date: Thu, 5 Aug 2021 15:25:35 +0000 Subject: Connectionists: Summer School on Network and Control Sciences for Psychiatry Message-ID: <6a7cab72-d277-7938-799f-de62d4ba2b79@posteo.de> Dear all, We are happy to announce a Summer School on ??? ?Current and Future Applications of Network and Control Sciences for Psychiatry? Host Institution: *University of T?bingen, Germany* Location: *Online event* Dates: *September 29th ? October 1st 2021* Abstract deadline: *September 1st, 2021* Registration fees: *free* *Focus* This Summer School gives an opportunity to students and young researchers to get acquainted with and exchange within a range of current topics in network and control sciences and its applications in Psychiatry. ____ *Keynotes* Peter Dayan (MPI T?bingen, Germany) John Medaglia (Drexel University, USA) Danielle S. Bassett (University of Pennsylvania, USA) For the full list of speakers visit: https://www.medizin.uni-tuebingen.de/de/summer-school-controlpsychiatry/speakers ____ *Registration* The summer school is free of charge for all participants, but to get all important information please register online via: https://www.medizin.uni-tuebingen.de/de/summer-school-controlpsychiatry ____ *Poster Submission* Participants can present their latest research results as a poster. Some of the most relevant submissions will have the possibility to present their work in a dedicated oral session and receive an official certificate. Please submit your abstract (limited to 250 words) latest by September 1st to: controlpsychiatry at med.uni-tuebingen.de ____ Questions? Please contact: controlpsychiatry at med.uni-tuebingen.de We are excited to see you soon! Best wishes, The organizing committee -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Flyer_Summer School 2021_ControlPsychiatry.pdf Type: application/pdf Size: 964039 bytes Desc: not available URL: From ghumana at upmc.edu Fri Aug 6 15:40:49 2021 From: ghumana at upmc.edu (Ghuman, Avniel) Date: Fri, 6 Aug 2021 19:40:49 +0000 Subject: Connectionists: Lab Manager Position in Visual Neuroscience using Human Intracranial Recordings in Pittsburgh, PA, USA Message-ID: The Laboratory of Cognitive Neurodynamics (LCND; PI: Avniel Ghuman) at the University of Pittsburgh is seeking a Lab Manager to start June 2021. The LCND studies how our brains turn what we see into the rich meaningful experience we perceive in the world around us. We use direct neural recordings in epilepsy patients (intracranial electroencepholography) and non-invasive magnetoencephalography to measure the neural response to objects, faces, words, and social and affective visual stimuli with millisecond temporal resolution. We combine these high fidelity recordings with advanced signal processing, network analysis, and machine learning to understand how information flows through the visual processing networks of our brain. We use these recordings and analysis methods together to understand the computations that allow the human brain to read, recognize faces, comprehend facial expressions and gestures, and recognize objects. Key responsibilities include assisting with experimental design, data collection, interfacing with the clinical epilepsy team, data preprocessing, and managing all aspects of lab life. Many opportunities exist to be involved with research at all levels, including having your own projects. The work involves extensive interaction with patients at their hospital bed, therefore a professional and empathetic bedside manner is critical as are strong organizational skills. We are looking for a bright, organized, empathetic, and driven candidate dedicated to neuroscience research. Candidates should have degree in neuroscience, biology, psychology, engineering, computer science or a related field, and familiarity with programming is highly desirable. Administrative experience managing Institutional Review Board protocols is preferred, but not required. Interested candidates please send a CV and a statement of interest to Dr. Avniel Ghuman (ghumana at upmc.edu) with the subject line ?Lab manager application.? Applications will be accepted until the position is filled. -------------- next part -------------- An HTML attachment was scrubbed... URL: From m.reske at fz-juelich.de Fri Aug 6 09:03:53 2021 From: m.reske at fz-juelich.de (Martina Reske) Date: Fri, 6 Aug 2021 15:03:53 +0200 Subject: Connectionists: Open PhD Position in Computational Neurosience in Juelich, Germany - Generic metadata management for reproducible high-performance-computing simulation workflows Message-ID: <3bd596d8-c5f8-8aca-4511-8fee9d785c0d@fz-juelich.de> The Institute of Neuroscience and Medicine - Computational and Systems Neuroscience (INM-6) at Research Center Juelich is also part of the Institute for Advanced Simulation (IAS-6, Theoretical Neuroscience) and hosts the Coordination Site (BCOS) of the national Bernstein Network Computational Neuroscience. Among other projects, the INM-6/IAS-6 participates in the EU flagship ?Human Brain Project? (HBP, https://humanbrainproject.eu). The institute creates mathematical models of the dynamics and function of neural circuits. This includes model-driven analysis of brain activity and structure, and simulation of biologically realistic models using high-performance computing (HPC) technology. A main challenge in this research field is the acquisition and organization of the metadata accompanying these simulations. This challenge will be addressed in an interdisciplinary project in Neuroscience and Environmental Research funded by the Helmholtz Metadata Collaboration (HMC, https://helmholtz-metadaten.de). The recently started project ?Generic metadata management for reproducible high-performance-computing simulation workflows? aims at developing a generic, cross-domain metadata management framework to foster reproducibility of HPC based simulation science, and to provide workflows and tools for an efficient organization, exploration and visualization of simulation data. A central goal of this project is to unify existing approaches, while at the same time developing concepts and tools that are applicable to diverse research fields and can cope with the modularity and flexibility demands of rapidly progressing science. This project is a collaboration between the Research Centre J?lich and the Helmholtz Centre for Environmental Research - UFZ, Leipzig. We at INM-6 are searching for a PhD candidate contributing to the development of a metadata management framework for generic HPC-based simulation science and in particular its application to the research field Computational Neuroscience. We are offering a PhD Position - Generic metadata management for reproducible high-performance-computing simulation workflows Your Job: The successful candidate will contribute to the project by designing, implementing, and evaluating a metadata management framework for a Computational Neuroscience use case. This includes: * Review of existing approaches and tools * Requirement specification * Conceptual design blueprint of implementation * Proof-of-concept application to Computational Neuroscience * Development of neuronal network models addressing Neuroscience questions * Simulations of neuronal networks using HPC infrastructure * Presentation and publication of the results * Close interaction with team members and collaborators from INM-6, the J?lich Supercomputing Centre (JSC) and the Helmholtz Centre for Environmental Research - UFZ * Exchange and networking within national (NFDI) and international (RDA, EOSC) initiatives and within the funding incubator platform HMC Your Profile: * Completed study (Diploma/Master) in Physics, Computer Science, Computational Neuroscience or a related field * Solid programming skills preferably in Python and/or C++; experience with Python libraries (e.g., NumPy, SciPy, Matplotlib, and pandas) is beneficial * Experience with software development (e.g., version control with Git) and data organization (e.g., data bases with SQL and MySQL) is preferable * Knowledge of relevant metadata standards and semantic techniques are beneficial * Experience with modeling, simulation, and analysis of complex systems * Keen interest in cognitive and systems neuroscience * Interest in interdisciplinary projects * Interest in collaborative work and good communication skills * Good command of English Our Offer: We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We offer ideal conditions for you to complete your doctoral degree: * A highly motivated working group as well as an international and interdisciplinary working environment at one of Europe?s largest research establishments * Outstanding scientific and technical infrastructure * Opportunity to participate in (international) conferences and project meetings * Continuous scientific mentoring by your scientific advisor * Flexible working hours and 30 days of annual leave * Further development of your personal strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the J?lich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de/judocs * Targeted services for international employees, e.g. through our International Advisory Service The position is initially for a fixed term of 3 Jahre years. Pay in line with 65 % of pay group 13 of the Collective Agreement for the Public Service (TV?D-Bund) and additionally 60 % of a monthly salary as special payment (?Christmas bonus?). Further information on doctoral degrees at Forschungszentrum J?lich including our other locations is available at: www.fz-juelich.de/gp/Careers_Docs Forschungszentrum J?lich promotes equal opportunities and diversity in its employment relations. We also welcome applications from disabled persons. Please apply via our online recruiting system until Sept 15th, 2021. Reference number: 2021D-107 Martina Reske -- Dr. Martina Reske Scientific Coordinator Institute of Neuroscience and Medicine (INM-6) Computational and Systems Neuroscience & Institute for Advanced Simulation (IAS-6) Theoretical Neuroscience J?lich Research Centre and JARA J?lich, Germany Work +49.2461.611916 Work Cell +49.151.26156918 Fax +49.2461.619460 www.csn.fz-juelich.de ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From mtkostecki at gmail.com Sun Aug 8 14:14:31 2021 From: mtkostecki at gmail.com (Mateusz Kostecki) Date: Sun, 8 Aug 2021 20:14:31 +0200 Subject: Connectionists: Preprogrammed: Innateness in Neuroscience and AI Symposium - dadline extended Message-ID: Dear colleagues, we are extending the deadline for the registration to our *Preprogrammed: Innateness in Neuroscience and AI *till August 25th. Please find all necessary information here - https://nenckiopenlab.org/innateness/ Best! Mateusz Kostecki -------------- next part -------------- An HTML attachment was scrubbed... URL: From gyguo95 at gmail.com Mon Aug 9 05:58:15 2021 From: gyguo95 at gmail.com (=?UTF-8?B?6YOt5bm/5a6H?=) Date: Mon, 9 Aug 2021 17:58:15 +0800 Subject: Connectionists: CFP: TMM SI Message-ID: One-week deadline for the upcoming special issue on IEEE T-MM.More detailed dates and scope of the special issue are listed below. Looking forward to your contribution! *SUMMARY:* With the goal of addressing fine-level image and video understanding tasks by learning from coarse-level human annotations, WSL is of particular importance in such a big data era as it can dramatically alleviate the human labor for annotating each of the structured visual/multimedia data and thus enables machines to learn from much larger-scaled data but with the equal annotation cost of the conventional fully supervised learning methods. More importantly, when dealing with the data from real-world application scenarios, such as the medical imaging data, remote sensing data, and audio-visual data, fine-level manual annotations are very limited and difficult to obtain. Under these circumstances, the WSL-based learning frameworks, specifically for the WSL-based multi-modality/multi-task learning frameworks, would bring great benefits. Unfortunately, designing effective WSL systems is challenging due to the issues of ?semantic unspecificity? and ?instance ambiguity?, where the former refers to the setting where the provided semantic label is at image level rather than specific instance-level while the latter refers to the ambiguity when determining an instance sample against the instance part or instance cluster. Principled solutions to address these problems are still under-studied. Nowadays, with the rapid development of advanced machine learning techniques, such as the Graph Convolutional Networks, Capsule Networks, Transformers, Generative Adversarial Networks, and Deep Reinforcement Learning models, new opportunities have emerged for solving the problems in WSL and applying WSL to richer vision and multimedia tasks. This special issue aims at promoting cutting-edge research along this direction and offers a timely collection of works to benefit researchers and practitioners. We welcome high-quality original submissions addressing both novel theoretical and practical aspects related to WSL, as well as the real-world applications based on WSL approaches. *SCOPE:* Topics of interests include, but are not limited to: - Multi-modality weakly supervised learning theory and framework; - Multi-task weakly supervised learning theory and framework; - Robust learning theory and framework; - Audio-visual learning under weak supervision; - Weakly supervised spatial/temporal feature learning; - Self-supervised learning frameworks and applications; - Graph Convolutional Networks/Graph Neural Networks-based weakly supervised learning frameworks; - Deep Reinforcement Learning for weakly supervised learning; - Emerging vision and multimedia tasks with limited supervision; *IMPORTANT DATESs: * Manuscript submission: 15th August 2021 Preliminary results: 15th November 2021 Revisions due: 1st January 2022 Notification: 15th February 2022 Final manuscripts due: 15th March 2022 Anticipated publication: Midyear 2022 *SUBMISSION PROCEDURE:* Papers should be formatted according to the IEEE Transactions on Multimedia guidelines for authors (see: http://www.signalprocessingsociety.org/tmm/tmm-author-info/). By submitting/resubmitting your manuscript to these Transactions, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay all over-length page charges, color charges, and any other charges and fees associated with publication of the manuscript. Manuscripts (both 1-column and 2-column versions are required) should be submitted electronically through the online IEEE manuscript submission system at http://mc.manuscriptcentral.com/tmm-ieee. All submitted papers will go through the same review process as the regular TMM paper submissions. Referees will consider originality, significance, technical soundness, clarity of exposition, and relevance to the special issue topics above. -- Dingwen Zhang https://zdw-nwpu.github.io/dingwenz.github.com/ Northwestern Polytechnical University -- Dingwen Zhang https://zdw-nwpu.github.io/dingwenz.github.com/ Northwestern Polytechnical University -------------- next part -------------- An HTML attachment was scrubbed... URL: From justin.svegliato at gmail.com Sun Aug 8 19:10:01 2021 From: justin.svegliato at gmail.com (Justin Svegliato) Date: Sun, 8 Aug 2021 19:10:01 -0400 Subject: Connectionists: [Final CFP] IROS Workshop on Building and Evaluating Ethical Robotic Systems (ERS 2021) Message-ID: Website: https://ers-workshop.com/ Submission Deadline: August 13, 2021 (AoE) Submission Link: https://easychair.org/conferences/?conf=ers2021 Contact: ers.workshop at gmail.com *===Workshop Overview===* The deployment of robotic systems has been accelerating in many domains that have a substantial impact on society. For example, robotic systems have been proposed for applications that range from elder care and autonomous driving to nuclear energy production and military technology. However, while our ability to build robotic systems that integrate into our daily lives has expanded over the years, it has outstripped our ability to build robotic systems that can account for the large number of different ethical considerations that may arise during operation. This workshop therefore focuses on building and evaluating ethical robotic systems at every level of the robotics stack while broadening the scope of areas that should be considered by researchers, such as how users can interact with new and existing technology or how legislators can develop actionable standards and regulations. *ERS 2021* aims to bring together researchers from academia and industry to discuss key challenges, learn from real-world case studies, identify potential research avenues, explore recent technical advances, present novel data sets, and survey existing work related to ethical robotic systems. Given this aim, we invite contributions that draw from a range of methods in artificial intelligence and robotics, such as planning, reinforcement learning, machine learning, deep learning, human-robot interaction, safety, explainability, transparency, formal verification, social preferences, and human factors. Most importantly, we welcome researchers from disciplines beyond robotics, including philosophy, psychology, sociology, and law, in order to represent diverse perspectives on building and evaluating ethical robotic systems. Relevant research topics include but are not limited to: - Value alignment in robotic systems - Cultural, political, and societal impacts of robotics - Methods for analyzing the ethical implications of autonomous systems - Moral reasoning in autonomous systems - Safe, transparent, explainable, or interpretable machine learning - Ethical compliance in robotic systems - Ethically sensitive design and implementation of autonomous systems - Human-compatible or beneficial AI systems - Law, regulation, and governance of robotics - Challenges of building and evaluating ethical robotic systems - Ethical models and algorithms in robotic systems - Impacts of robotics on vulnerable groups - Novel data sets or test suites for ethical robotic systems *===Workshop Format===* This is a virtual IROS workshop that will include invited speakers, oral presentations of accepted papers, poster sessions of accepted papers, discussion sessions, and moderated panels. *===Submission Guidelines===* We encourage a range of submission types to facilitate broad participation: - Highlight Paper (up to 2 pages) - Short Technical Paper (up to 4 pages) - Full Technical Paper (up to 6 pages) - Position Paper (up to 4 pages) - Case Study Paper (up to 6 pages) - Survey Paper (up to 8 pages) Details: There is no page limit for references and supplementary materials. Submissions should be in PDF and follow the IROS 2021 format guidelines. All accepted papers will be included in an electronic, non-archival proceedings. Note that papers published, accepted, or under review at other conferences may be submitted and presented at the workshop subject to the conference guidelines. *===Best Paper Award===* The Center for Human-Compatible AI (CHAI) at UC Berkeley and the Berkeley Existential Risk Initiative (BERI) are generously sponsoring the *ERS 2021 Best Paper Award*. The best paper will be selected based on a vote among the organizers and the program committee. The authors of the best paper will receive a $400 cash prize and a printed certificate at the end of the workshop. *===Important Dates===* - Paper Submission: August 13, 2021 (AoE) - Author Notification: August 25, 2021 - Camera-Ready Submission: TBD *===Invited Speakers===* - Ron Arkin, Georgia Tech - Francesca Rossi, IBM - Matthias Scheutz, Tufts University - Ben Kuipers, University of Michigan - Bertram Malle, Brown University *===Organizers===* - Paul Bello, Naval Research Laboratory - Louise Dennis, University of Manchester - Dylan Hadfield-Menell, MIT - Samer Nashed, UMass Amherst (Co-Chair) - Justin Svegliato, UMass Amherst (Co-Chair) - Alan Winfield, UWE Bristol -------------- next part -------------- An HTML attachment was scrubbed... URL: From tat at tchumatchenko.de Sun Aug 8 16:08:01 2021 From: tat at tchumatchenko.de (Tatjana Tchumatchenko) Date: Sun, 8 Aug 2021 22:08:01 +0200 Subject: Connectionists: Open Postdoc and PhD positions in comp neuro (PI TatjanaTchumatchenko ) Message-ID: The Tchumatchenko Group is seeking PhD and Postdoc candidates to conduct research in the field of computational neuroscience. The group is one of the vibrant computational neuroscience in Germany and Europe and obtained competitive third party funding from the German Research Foundation and other funding schemes. The PhD candidate will be involved in a computational project which will be conducted in collaboration with the lab of Dr. Marcel Oberlaender at the Caesar Institute. This project will address how pyramidal neurons encode tactile information and will involve data analysis as well as recurrent network simulations in order to understand how spiking activity in the barrel cortex implements texture encoding. The Postdoc candidate will be involved in a research project addressing recurrent spiking networks with multi-spike plasticity rules and protein dynamics. Both projects are focused on computational tools and include pen-and-paper calculations, data analysis, and numerical simulations and require an interdisciplinary mindset. The ideal candidates are highly motivated, team-oriented graduates with a degree in life sciences, Physics, Mathematics, Biology, Engineering or similar disciplines with a strong interest in computational neuroscience. Prior experience with computational modelling techniques or neuroscience is advantageous, but not a strict requirement. Candidates should hold a diploma or a master?s degree (a PhD degree is required for the Postdoc position) and be enthusiastic about working in a competitive interdisciplinary research team. Good communication skills, a strong work ethic, excellent command of the English language are essential as well as the ability to work remotely during a pandemic and the willingness to travel to visit experimental collaborators as well as national and international conferences (whenever corona regulations allow). Qualified female candidates are particularly encouraged to apply. The salary will be according to the German public employee salary scale, start date negotiable. Please send your application with a cover letter, a CV with contact details from two references and copies of all relevant degree certificates to tatjana.tchumatchenko at uni-bonn.de. We are looking forward to your application! www.tchumatchenko.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.rapela at ucl.ac.uk Mon Aug 9 08:14:33 2021 From: j.rapela at ucl.ac.uk (Joaquin Rapela) Date: Mon, 9 Aug 2021 13:14:33 +0100 Subject: Connectionists: Job: research software engineer @ SWC/GCNU Message-ID: <20210809121433.GA2086144@u237c.id.gatsby.ucl.ac.uk> Hello list, I am the first member of the newly established Data Center of the Gatsby Computational Neuroscience Unit (GCNU) and Sainsbury Wellcome Centre (SWC). The GCNU develops state-of-the-art neural data analysis and machine learning algorithms. The SWC performs sophisticated neuroscience experiments, and records unprecedented behavioral and neural data. Combining these data analysis methods and these behavioral and neural recordings we will revolutionize our understanding of how computation in neural circuits gives rise to behavior. The Data Center is growing and is looking for a research engineer; details appear below. Please contact Tom Mrsic-Flogel (https://www.sainsburywellcome.org/web/people/tom-mrsic-flogel), director of the SWC, or send me an email, if you have any question about this position. Cordially, Joaquin RESEARCH SOFTWARE ENGINEER - BEHAVIOUR AND NEURAL DATA The Sainsbury Wellcome Centre and the Gatsby Computational Neuroscience Unit are looking for a proactive and creative Research Software Engineer to join the technical team in a newly established Data Centre. This is an exciting opportunity to play a key role in establishing data architectures and data processing pipelines for efficient querying of complex, large-scale and multi-format datasets of neural and behavioural data. Your work will directly contribute to our efforts to understand how the brain generates flexible, intelligent behaviour. The role will include developing, training and supervising a small team of research engineers to assist with the implementation of the software design and documentation. You will have a collaborative approach to work and the ability to build strong working relationships with colleagues to deliver successful research outcomes. Working alongside our IT team, you will create data management workflows for internal users and for sharing of data with the international research community. You will work closely with neuroscientists, electrical and mechanical engineers to design large-scale data collection, analysis and interactive visualization systems for next generation brain data. You will have advanced experience with systems programming languages and substantial experience in Python, NumPy or MATLAB. Substantial experience and knowledge of software development best practice including testing, documentation and version control is essential. With a competitive salary and benefits, this post is full time and funded until 31 October 2025 in the first instance. For further details download the information for candidates (https://www.sainsburywellcome.org/web/sites/default/files/2021-07/Job%20Description%20and%20Person%20Specification%20-%20Research%20Software%20Engineer%20-%201877801.pdf). To apply visit UCL's vacancy listings and search for the advert using reference number 1877608. Click on "Apply Now" at the bottom of the advert to enter the online recruitment portal. The deadline for applications is Sunday 22 August 2021. From franciscocruzhh at gmail.com Mon Aug 9 07:46:07 2021 From: franciscocruzhh at gmail.com (Francisco Cruz) Date: Mon, 9 Aug 2021 21:46:07 +1000 Subject: Connectionists: Call for Participation - Free Workshop on Human-aligned Reinforcement Learning for Autonomous Agents and Robots Message-ID: **Workshop on Human-aligned Reinforcement Learning for Autonomous Agents and Robots** @IEEE International Conference on Developmental and Learning ICDL 2021 Virtual conference Date: August 27th, 2021 Website: https://harlworkshop.github.io/ Registration is for free. Please register at https://registrationharl.eventbrite.com.au/ **Confirmed list of Speakers:** - Matthew Taylor, University of Alberta, Canada. - Alessandra Sciutti, IIT, Italy. - Bradley Knox, Bosch, USA. - Peter Vamplew, Federation University, Australia. - Patrick Pilarski, DeepMind / University of Alberta, Canada. - George Konidaris, Brown University, USA. - Jens Kober, Delft University of Technology, The Netherlands. - Bruno Fernandes, University of Pernambuco, Brazil. - Benjamin Rosman, University of the Witwatersrand, South Africa. - Felipe Leno da Silva, Lawrence Livermore National Lab, USA. - Stefan Wermter, University of Hamburg, Germany. - Richard Dazeley, Deakin University, Australia. **Organizers:** Francisco Cruz (School of Information Technology, Deakin University, Australia) Thommen George Karimpanal (Applied Artificial Intelligence Institute, Deakin University, Australia) Miguel Solis (Facultad de Ingenier?a, Universidad Andr?s Bello, Chile) Pablo Barros (Cognitive Architecture for Collaborative Technologies Unit, Istituto Italiano di Tecnologia, Italy) Richard Dazeley (Machine Intelligence Lab, Deakin University, Australia) -------------- next part -------------- An HTML attachment was scrubbed... URL: From sanjay.ankur at gmail.com Mon Aug 9 10:05:29 2021 From: sanjay.ankur at gmail.com (Ankur Sinha) Date: Mon, 9 Aug 2021 15:05:29 +0100 Subject: Connectionists: NeuroML tutorials at INCF Training week: 23/26 August 2021 Message-ID: <20210809140529.gkxc4ku26zq2cdj5@ankur.workstation> Dear all, Apologies for the cross posts. We will be conducting a NeuroML tutorial at the upcoming INCF training week at the end of August. This tutorial is intended for members of the research community interested in learning more about how NeuroML and its related technologies facilitates the standardization, sharing, and collaborative development of models. This tutorial will be offered twice during the Neuroinformatics Training Week: session 1 is targeted to participants residing in Europe, Africa, and the Americas while session 2 is targeted at participants residing in Asia and Australia. Session 1: 23 Aug 2021, 11:00-15:00 EDT / 17:00-21:00 CEST Session 2: 26 Aug 2021, 09:00-13:00 CEST / 16:00-20:00 JST / 17:00-21:00 AEST Registration is free for INCF members. For non-members, registration is only $20 for students and postdocs, and $50 for others. Please register here: https://www.incf.org/virtual-incf-neuroinformatics-training-week-2021 More information on the tutorial, including the topics to be covered can be found here: https://docs.neuroml.org/Events/202108-INCF-Training-Week.html -- Thanks, Regards, Ankur Sinha (He / Him / His) Research Fellow at the Silver Lab | http://silverlab.org/ Department of Neuroscience, Physiology, & Pharmacology University College London, London, UK Time zone: Europe/London From jarenas at ing.uc3m.es Tue Aug 10 04:23:52 2021 From: jarenas at ing.uc3m.es (JERONIMO ARENAS GARCIA) Date: Tue, 10 Aug 2021 10:23:52 +0200 Subject: Connectionists: Postdoctoral position available at University Carlos III de Madrid, Spain Message-ID: *Postdoctoral Researcher in Natural Language Processing with experience in software development based on microservices* We are looking for a highly-motivated doctor to join the UC3M team working in the European IntelComp project (https://intelcomp.eu/). The role of the selected candidate will involve research on Natural Language Processing for Science, Technology and Innovation (STI)-related texts, SW implementation for dockerized environments, as well as support in the technical coordination of the project. *IntelComp project description:* The objective of IntelComp is to deliver a platform that provides tools for assisting the whole spectrum of STI policy, i.e., agenda setting, modeling design, implementation, monitoring and evaluation. It will do so by involving multi-disciplinary teams to co-develop innovative analytics services, Natural Language Processing pipelines and Artificial Intelligence workflows and by exploiting open data, services and computational resources from the EOSC, HPC environments and federated distributed operations at the European Union, national and regional level. IntelComp will adopt a living labs approach, targeting the following three domains: Artificial Intelligence, Climate Change and Health. *Research Group:* The Machine Learning for Data Science (ML4DS) research group of University Carlos III de Madrid has a background of over 20 years in R+D+i in the field of Machine Learning and its applications to Data Analysis and Information Processing. It is a reference in Spain as an early adopter and developer of cutting edge technologies, and their transfer to society through numerous research projects and contracts with companies from the private sector. It is currently working on important challenges to make Machine Learning more scalable and accessible to the final users. IntelComp is aligned with these objectives, since it addresses the training of models with tens of millions of documents from the STI field, and the implementation of tools to facilitate the construction of these models by experts from a variety of research fields. *Responsibilities:* - Design and application of analysis algorithms based on topic models and graphs. Algorithm parallelization and GPU-based implementation. - Design of procedures to facilitate the construction and use of topic models and graphs by domain experts (AI, climate change, health), and the construction of analysis tools by the end users of the platform (policy makers). - Participation in the living labs of the project. - Deployment in microservices-based environments (docker, kubernetes). - Automation and parallelization of corpus generation processes: crawling subsystems, ingestion in the project database, etc. - Application of preprocessing techniques for documents and texts, automatic translation pipelines and natural language preprocessing, etc. - Dissemination of results through research papers, participation in dissemination sessions, workshops, etc. *Candidate profile: * - PhD in Natural Language Processing or similar. - Excellent research record in these areas: Machine Learning, Natural Language Processing, Topic Modeling, ML applications for STI, ML with graphs. - Demonstrable contributions to SW projects in the aforementioned areas. - Python expertise, especially with NLP and ML libraries (scikit-learn, pandas, Dask, nltk, spaCy, etc.), as well as Deep Learning (pytorch, tensorflow). - Advanced knowledge of web-oriented programming languages and libraries (JavaScript, D3.js ...). - Advanced knowledge of databases (SQL, MongoDB ...). - Experience in software development / integration in dockerized environments. DevOps experience (kubernetes, ansible) oriented to SW development (not systems administration). - Awards and other academic distinctions. *Description of job position and benefits:* - Gross salary of 37972,44 EUR/year - Employment 1 year with the possibility of extension for a second year. - Work on a multidisciplinary project made up of 13 beneficiary teams from different countries and varied profiles (ML, NLP, HPC, STI experts, policy makers consultants and implementers, etc.). - Economic support for professional related travel and research needs. *Applications must be received by September 6th, 2021.* The position will start on October 1st, 2021 (starting date is flexible). *Further information:* Dr. Jer?nimo Arenas-Garc?a: jarenas at ing.uc3m.es *Application:* Additional information is provided here . Applications need to be submitted electronically through the UC3M website accompanied by: - Copy of National Identity document or passport - Curriculum and supporting documentation of the merits provided - Copy of PhD degree title -- JERONIMO ARENAS GARCIA Universidad Carlos III de Madrid -------------- next part -------------- An HTML attachment was scrubbed... URL: From dayan.eran at gmail.com Mon Aug 9 07:35:13 2021 From: dayan.eran at gmail.com (Eran Dayan) Date: Mon, 9 Aug 2021 07:35:13 -0400 Subject: Connectionists: Postdoctoral Research Associate position in deep learning at UNC Chapel Hill Message-ID: A Postdoctoral Research Associate position is immediately open in the Neuroinformatics lab (dayanlab.web.unc.edu) at the Biomedical Research Imaging Center, University of North Carolina at Chapel Hill. The position is open to accomplished and highly motivated candidates, with an interest in machine learning and clinical neuroscience. The lab focuses on fundamental questions relating to brain organization in neurodegenerative diseases, while aiming to develop methods and tools that could eventually be used in the clinic. The Postdoctoral Research Associate will develop diagnostic and prognostic deep learning models for Alzheimer?s disease using rich existing multimodal datasets. Ample training and career development opportunities will be provided, as well as opportunities to collaborate with other groups within and outside UNC. A recent (<2 years) doctoral degree in biomedical engineering, computer science, computational neuroscience, biomedical data science, physics or other related fields is required. Excellent quantitative background, experience in deep learning, relevant programming experience, and a track record of first-author publications in peer-reviewed journals are required. Interest and experience in clinical neuroscience, particularly in Alzheimer?s disease research, would be advantageous but is not required. To apply, please send your C.V, and the names and contact details of at least 2 referees to Dr. Eran Dayan at: eran_dayan at med.unc.edu The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, race, national origin. -------------- next part -------------- An HTML attachment was scrubbed... URL: From junfeng989 at gmail.com Mon Aug 9 21:30:48 2021 From: junfeng989 at gmail.com (Jun Feng) Date: Tue, 10 Aug 2021 09:30:48 +0800 Subject: Connectionists: [Submission Deadline: Sep. 1][10+ Special Issues] CFP IEEE DependSys 2021: The 7th IEEE International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications, Dec. 17-19, Haikou, China Message-ID: [Apologies if you receive multiple copies of this message] Call For Papers ============================================================================= CFP IEEE DependSys 2021 The 7th IEEE International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications Dec. 17-19, Haikou, China [Submission Deadline: Sep. 1][10+ Special Issues] http://www.ieee-cybermatics.org/2021/dependsys/ IEEE DependSys 2021 conference is the 7th event in the series of conferences which offers a timely venue for bringing together new ideas, techniques, and solutions for dependability and its issues in sensor, cloud, and big data systems and applications. As we are deep into the Information Age, huge amounts of data are generated every day from sensors, individual archives, social networks, Internet of Things, enterprises and Internet in various scales and format which will pose a major challenge to the dependability of our designed systems. As these systems often tend to become inert, fragile, and vulnerable after a period of running. Effectively improving the dependability of sensor, cloud, big data systems and applications has become increasingly critical. This conference provides a forum for individuals, academics, practitioners, and organizations who are developing or procuring sophisticated computer systems on whose dependability of services they need to place great confidence. Future systems need to close the dependability gap in face of challenges in different circumstances. The emphasis will be on differing properties of such services, e.g., continuity, effective performance, real-time responsiveness, ability to overcome data fault, corruption, anomaly, ability to avoid catastrophic failures, prevention of deliberate privacy intrusions, reliability, availability, sustainability, adaptability, heterogeneity, security, safety, and so on. ============================================================================= IEEE DependSys 2021 is sponsored by IEEE, IEEE Computer Society, and IEEE Technical Committee on Scalable Computing (TCSC). All accepted papers will be submitted to IEEE Xplore and Engineering Index (EI). Best Paper Awards will be presented to high quality papers. Distinguished papers, after further revisions, will be published in 10+ SCI & EI indexed prestigious journals (confirmed). 1. IEEE Transactions on Intelligent Transportation Systems SI on Graph-based Machine Learning for Intelligent Transportation Systems https://ad051eeb-2ac9-4983-9271-c88f64105e50.filesusr.com/ugd/eaf218_db671bf4e4eb4a41ac1cf6da14a77750.pdf 2. IEEE Transactions on Intelligent Transportation Systems SI on Data Science for Cooperative Intelligent Transportation Systems https://ad051eeb-2ac9-4983-9271-c88f64105e50.filesusr.com/ugd/eaf218_de7a6f420a2b4c6d894e4de63e495624.pdf 3. IEEE Transactions on Network Science and Engineering SI on The Nexus Between Edge Computing and AI for 6G Networks https://www.comsoc.org/publications/journals/ieee-tnse/cfp/nexus-between-edge-computing-and-ai-6g-networks 3. IEEE/ACM Transactions on Computational Biology and Bioinformatics SI: Deep Learning-Empowered Big Data Analytics in Biomedical Applications and Digital Healthcare https://www.computer.org/digital-library/journals/tb/call-for-papers-special-issue-on-deep-learning-empowered-big-data-analytics-in-biomedical-applications-and-digital-healthcare 5. Security and Communication Networks SI on Protocols, Technologies, and Infrastructures for Secure Mobile Video Communications https://www.hindawi.com/journals/scn/si/926306/ 6. MDPI Sensors SI on Recent Advances in Algorithm and Distributed Computing for the Internet of Things https://www.mdpi.com/journal/sensors/special_issues/Algorithm_Distributed_Computing_IOT 7. International Journal of Distributed Sensor Networks SI: Privacy-Preserving Solutions in the Internet of Things https://journals.sagepub.com/page/dsn/collections/special-issues/privacy-preserving-solutions-in-the-internet-of-things 8. IET Communications SI on Intelligent Metasurfaces for Smart Connectivity https://digital-library.theiet.org/files/IET_COM_CFP_IMSC.pdf 9. Building and Environment SI: AI and IoT Applications of Smart Buildings and Smart Environment Design, Construction and Maintenance https://www.journals.elsevier.com/building-and-environment/call-for-papers/ai-and-iot-applications-of-smart-buildings-and-smart-environment-design-construction-and-maintenance 10. Journal of Systems Architecture SI: Cloud-Edge-End Architecture for Internet of Things Applications https://www.journals.elsevier.com/journal-of-systems-architecture/call-for-papers/special-issue-on-cloud-edge-end-architecture-for-internet-of-things-applications-vsi-cloud-edge-end-iot 11. Information SI: "Crossing ?Data, Information, Knowledge, and Wisdom? Models?Challenges, Solutions, and Recommendations" https://www.mdpi.com/journal/information/special_issues/DIKW_RA_2021 * More special issues will be added later. ================== Important Dates ================== Workshop Proposal Due: 1 August, 2021 Paper Submission Deadline: 1 September, 2021 Authors Notification: 1 October, 2021 Final Manuscript Due: 1 November, 2021 Conference Date: 17-19 December, 2021 ================== Topics of interest include, but are not limited to ================== Track 1: Dependability and Security Fundamentals and Technologies - Concepts, theory, principles, standardization and modelling, and methodologies - Dependability of sensor, wireless, and Ad-hoc networks, software defined networks - Dependability issues in cloud/fog/edge - Security and privacy - Security/privacy in cloud/fog/edge - Homomorphic encryption, differential privacy - Blockchain security - Artificial intelligence - Big data foundation and management - Dependable IoT supporting technologies Track 2: Dependable and Secure Systems - Dependable sensor systems - Dependability and availability issues in distributed systems - Cyber-physical systems (e.g. automotive, aerospace, healthcare, smart grid systems) - Database and transaction processing systems - Safety and security in distributed computing systems - Self-healing, self-protecting, and fault-tolerant systems - Dependability in automotive systems - Dependable integration - Dependability in big data systems - Software system security Track 3: Dependable and Secure Applications - Sensor and robot applications - Big data applications - Cloud/fog/edge applications - Datacenter monitoring - Safety care, medical care and services - Aerospace, industrial, and transportation applications - Energy, smart grid, IoT, CPS, smart city, and utility applications - Decentralized applications, federated learning applications - Mobile sensing applications, detection and tracking Track 4: Dependability and Security Measures and Assessments - Dependability metrics and measures for safety, trust, faith, amenity, easiness, comfort, and worry - Levels and relations, assessment criteria and authority - Dependability measurement, modeling, evaluation, and tools - Dependability evaluation - Software and hardware reliability, verification and validation - Evaluations and tools of anomaly detection and protection in sensor, cloud, big data systems ================== Paper Submission ================== All papers need to be submitted electronically through the conference submission website (https://edas.info/N28864) with PDF format. The materials presented in the papers should not be published or under submission elsewhere. Each paper is limited to 8 pages (or 10 pages with over length charge) including figures and references using IEEE Computer Society Proceedings Manuscripts style (two columns, single-spaced, 10 fonts). You can confirm the IEEE Computer Society Proceedings Author Guidelines at the following web page: http://www.computer.org/web/cs-cps/ Manuscript Templates for Conference Proceedings can be found at: https://www.ieee.org/conferences_events/conferences/publishing/templates.html Once accepted, the paper will be included into the IEEE conference proceedings published by IEEE Computer Society Press (indexed by EI). At least one of the authors of any accepted paper is requested to register the paper at the conference. ================== Organizing Committee ================== General Chairs - Stephen S. Yau, Arizona State University, USA - Zheng Yan, Xidian University, China and Aalto University, Finland - Willy Susilo, University of Wollongong, Australia Program Chairs - Bin Song, Xidian University, China - Mamoun Alazab, Charles Darwin University, Australia - Jun Feng, Huazhong University of Science and Technology, China Steering Committee - Jie Wu, Temple University, USA (Chair) - Md Zakirul Alam Bhuiyan, Fordham University, USA (Chair) - Guojun Wang, Guangzhou University, China - Vincenzo Piuri, University of Milan, Italy - Jiannong Cao, Hong Kong Polytechnic University, Hong Kong - Laurence T. Yang, St. Francis Xavier University, Canada - Sy-Yen Kuo, National Taiwan University, Taiwan - Yi Pan, Georgia State University, USA - A. B. M Shawkat Ali, The University of Haikou, China, Haikou, China - Mohammed Atiquzzaman, University of Oklahoma, USA - Al-Sakib Khan Pathan, Southeast University, Bangladesh - Kenli Li, Hunan University, China - Shui Yu, University of Technology Sydney (UTS), Australia - Yang Xiang, Swinburne University of Technology, Australia - Kim-Kwang Raymond Choo, The University of Texas at San Antonio, USA - Kamruzzaman Joarder, Federation University and Monash University, Australia -- Dr. Jun Feng Huazhong University of Science and Technology Mobile: +86-18827365073 WeChat: junfeng10001000 E-Mail: junfeng989 at gmail.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From david at irdta.eu Mon Aug 9 15:50:08 2021 From: david at irdta.eu (David Silva - IRDTA) Date: Mon, 9 Aug 2021 21:50:08 +0200 (CEST) Subject: Connectionists: DeepLearn 2022 Winter: early deadline August 22 Message-ID: <1079441104.1127093.1628538608340@webmail.strato.com> ****************************************************************** 5th INTERNATIONAL SCHOOL ON DEEP LEARNING DeepLearn 2022 Winter Bournemouth, UK January 17-21, 2022 Co-organized by: Department of Computing and Informatics Bournemouth University Institute for Research Development, Training and Advice ? IRDTA Brussels/London https://irdta.eu/deeplearn2022w/ ****************************************************************** Early deadline: August 22, 2021 ****************************************************************** SCOPE: DeepLearn 2022 Winter will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw and Las Palmas de Gran Canaria. Deep learning is a branch of artificial intelligence covering a spectrum of current exciting research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of different environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, image analysis, recommender systems, advertising, fraud detection, robotics, games, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience. Most deep learning subareas will be displayed, and main challenges identified through 24 four-hour and a half courses and 3 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main components of the event. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2022 Winter is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2022 Winter will take place in Bournemouth, a coastal resort town on the south coast of England. The venue will be: TBA STRUCTURE: 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Full in vivo online participation will be possible. However, the organizers want to emphasize the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Yi Ma (University of California, Berkeley), White-box Deep (Convolution) Networks from First Principles Daphna Weinshall (Hebrew University of Jerusalem), Curriculum Learning in Deep Networks Eric P. Xing (Carnegie Mellon University), TBA PROFESSORS AND COURSES: Peter L. Bartlett (University of California, Berkeley), [intermediate/advanced] Deep Learning: A Statistical Viewpoint Joachim M. Buhmann (Swiss Federal Institute of Technology, Z?rich), [introductory/advanced] Algorithm Validation for Data Science Nitesh Chawla (University of Notre Dame), [introductory/intermediate] Graph Representation Learning Seungjin Choi (BARO AI Academy), [introductory/intermediate] Bayesian Optimization over Continuous, Discrete, or Hybrid Spaces Sumit Chopra (New York University), [intermediate] Deep Learning in Healthcare R?diger Dillmann (Karlsruhe Institute of Technology), [introductory/intermediate] Building Brains for Robots Marco Duarte (University of Massachusetts, Amherst), [introductory/intermediate] Explainable Machine Learning Charles Elkan (University of California, San Diego), [intermediate] AI and ML Applications in Finance and Retail Rob Fergus (New York University), [intermediate/advanced] Self-supervised Learning of Visual Representations for Recognition and Interaction Jo?o Gama (University of Porto), [introductory] Learning from Data Streams: Challenges, Issues, and Opportunities Mark Girolami (University of Cambridge), [introductory/intermediate] Computational Statistics and Machine Learning Claus Horn (Zurich University of Applied Sciences), [intermediate] Deep Learning for Biotechnology Nathalie Japkowicz (American University), [intermediate/advanced] Learning from Class Imbalances Gregor Kasieczka (University of Hamburg), [introductory/intermediate] Deep Learning Fundamental Physics: Rare Signals, Unsupervised Anomaly Detection, and Generative Models Karen Livescu (Toyota Technological Institute at Chicago), [intermediate/advanced] Speech Processing: Automatic Speech Recognition and beyond David McAllester (Toyota Technological Institute at Chicago), [intermediate/advanced] Information Theory for Deep Learning Dhabaleswar K. Panda (Ohio State University), [intermediate] Exploiting High-performance Computing for Deep Learning: Why and How? Tomaso Poggio (Massachusetts Institute of Technology), [advanced] Deep Learning: Theoretical Observations Fabio Roli (University of Cagliari), [introductory/intermediate] Adversarial Machine Learning Jude W. Shavlik (University of Wisconsin, Madison), [introductory/intermediate] Advising, Explaining, Distilling, and Quantizing Deep Neural Networks Kunal Talwar (Apple), [introductory/intermediate] Foundations of Differentially Private Learning Lyle Ungar (University of Pennsylvania), [intermediate] Natural Language Processing using Deep Learning Yu-Dong Zhang (University of Leicester), [introductory/intermediate] Convolutional Neural Networks and Their Applications to COVID-19 Diagnosis OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by January 9, 2022. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by January 9, 2022. EMPLOYER SESSION: Firms searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by January 9, 2022. ORGANIZING COMMITTEE: Rashid Bakirov (Bournemouth, co-chair) Nan Jiang (Bournemouth, co-chair) Carlos Mart?n-Vide (Tarragona, program chair) Sara Morales (Brussels) David Silva (London, co-chair) REGISTRATION: It has to be done at https://irdta.eu/deeplearn2022w/registration/deeplearn-2022/ The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will get exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. ACCOMMODATION: Accommodation suggestions will be available in due time at https://irdta.eu/deeplearn2022w/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: Bournemouth University Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From sigurd.lokse at uit.no Tue Aug 10 11:00:08 2021 From: sigurd.lokse at uit.no (=?utf-8?B?U2lndXJkIEVpdmluZHNvbiBMw7hrc2U=?=) Date: Tue, 10 Aug 2021 15:00:08 +0000 Subject: Connectionists: =?utf-8?q?2nd_Call_for_Contributions=3A_5th_North?= =?utf-8?q?ern_Lights_Deep_Learning_Conference=2C_10-12_January_2022=2C_Tr?= =?utf-8?b?b21zw7ggKCJOb3J0aCBQb2xlIiksIE5vcndheS4=?= Message-ID: Following tradition, we are organizing the 5th Northern Lights Deep Learning Conference (NLDL) on 10-12 January 2022 in Troms?, Norway. We invite submissions presenting new and original research on all aspects of Deep Learning. The topics include but are not limited to the following: * Architecture, concepts and optimization * Deep learning for structured and unstructured data * Graph neural networks * Generative models * Bayesian Deep Learning * Lightweight / frugal Deep Learning * Explainability and interpretability of Deep Learning models * Computer vision * Natural language processing * Deep Learning for signals, images, 3D and hyperspectral images * Deep Learning applications to biology and medicine * Deep Learning application to environment and ecology * Deep Learning applications to Physics * Deep Learning for industrial applications On the 10th of January, a mini deep learning school in form of tutorials will be held, followed by the main conference on the 11th and 12th. Please see http://www.nldl.org for more information. As always, we are happy to have top international speakers. This year, for instance * Serge Belongie from Cornell University and Copenhagen University * Zeynep Akata from the University of T?bingen and Max Planck Institute for Informatics * Sophia Ananiadou from the University of Manchester * Pierre Baldi from the University of California, Irvine and more to come. We are accepting two alternatives for contributions: (1) Full paper submissions (6 pages) will be presented either as orals or as posters and will be published in the conference proceedings**; (2) Extended abstracts (2 pages) will be presented either as orals or as posters (but not published in the conference proceedings). The review process is double-blind. Deadline for both types of submissions: October 15th, 2021. Instructions on template etc. can be found on http://www.nldl.org. We hope to see many participants for a nice scientific gathering on the "north pole", including social events, and hopefully some northern lights ? ** The Proceedings of NLDL are approved as a level 1 publication in the Norwegian national list of authorized research publication channels. Kind regards, The NLDL 2022 organizing committee. -------------- next part -------------- An HTML attachment was scrubbed... URL: From cognitivium at sciencebeam.com Tue Aug 10 05:19:41 2021 From: cognitivium at sciencebeam.com (Mary) Date: Tue, 10 Aug 2021 13:49:41 +0430 Subject: Connectionists: FINAL call to register for the IBRO School of Neuroscience workshops Message-ID: <202108100919.17A9Jlaf080101@scs-mx-04.andrew.cmu.edu> Dear Researchers, This is a kindly reminder that the registration deadline (August 15th) for the IBRO-APRC Georgian Associate School of Neuroscience workshops are approaching, and won?t be extended again. 1. "Multi-channel/Multi-unit Recording in Behaving Mice" workshop: ? Theoretical Section: ? Preparation of multichannel recordings electrodes/tetrodes ? Animal surgeries/multichannel/multi-unit recordings ? Data acquisition and storing ? Practical Section: ? Pain Management Description: The overall goal of this experiment is demonstration of a general framework for the peripheral nervous system (PNS) recording via the eLab recording system which is manufactured by ScienceBeam company. We are going to conduct an animal experiment on Sciatic nerve branches such as Tibial and Peroneal nerve to detect nociceptive pain induced by noxious mechanical stimulation in ipsilateral paw. (Watch what you?ll learn: https://www.youtube.com/watch?v=yFhQOt71xjQ&feature=emb_title ) ? Locomotion Management Description: The overall goal of the following experiment is to use the eLab system for recording and electrical stimulation of the spinal cord in order to control hindlimb kinematic in the rat model. This is achieved by delicately removing the skin and muscle layers over the spinal column and identifying the correct vertebral target. Next, a laminectomy is performed on the targeted vertebra to expose the spinal cord. Then microelectrode is implanted on the spinal segments to record neural activity such as local field potential and spike to decode air-stepping motion or deliver electrical pulses to manage hindlimb locomotion. (Watch what you?ll learn: https://www.youtube.com/watch?v=3uA3OCojlQE&feature=emb_title ) ? More information and registration: https://sciencebeam.com/multi-channel-multi-unit-recording-in-behaving-mice/ 2. "EEG/ERP Recording and Analysis" workshop: Through the lecture, you will learn about the basics of EEG signal, how to record it, and different approaches to EEG signal processing, that are more or less commonly adopted in cognitive neuroscience. You will learn about EEG signal pre-processing and how to compute ERPs, Microstates, and Time-frequency maps as a function of experimental manipulations and designs. This will be illustrated by case studies in the electrophysiology of language. There will be a focus on critical thinking about the choices of analyses as a function of research questions, challenges depending on experimental designs, and parameters to pay attention to. At the end of the lecture, you will know the strengths and weaknesses of these tools and will be able to decide which measure would be best adapted to your scientific investigations about cognition. ? More information and registration: https://sciencebeam.com/eeg-erp-recording-and-analysis/ If you require any further information, please contact us at: workshop at sciencebeam.com Mary Reae Human Neuroscience Department Manager www.ScienceBeam.com WhatsAppno: 008613380781282 -------------- next part -------------- An HTML attachment was scrubbed... URL: From julia.vogt at inf.ethz.ch Tue Aug 10 11:29:47 2021 From: julia.vogt at inf.ethz.ch (Vogt Julia) Date: Tue, 10 Aug 2021 15:29:47 +0000 Subject: Connectionists: CfP for NeurIPS 2021 Workshop Bridging the Gap: from Machine Learning Research to Clinical Practice Message-ID: <4C1BE4ED-8877-41D0-AF36-BEEF61926147@inf.ethz.ch> We are pleased to announce the NeurIPS 2021 Workshop Bridging the Gap: from Machine Learning Research to Clinical Practice Call for Papers: https://sites.google.com/g.harvard.edu/research2clinics/call-for-papers About the workshop: In this workshop, we aim to bring together ML researchers and clinicians to discuss the challenges and potential solutions on how to enable the use of state-of-the-art ML techniques in the daily clinical practice and ultimately improve healthcare. We invite submissions describing innovative research focused on bridging the gap between ML research and application in clinical practice. Authors are invited to submit works that fit anywhere within the broad overview of our workshop. To incentivize high-quality submissions of novel work, which should be compelling and highly relevant to research and clinics, we will be awarding Best Paper Awards We are specifically interested (but are not limited to) the following areas: * Procedures that bring humans-in-the-loop for auditing ML healthcare systems to improve human performance, machine performance, or both. * Methods that are robust to changes in population, distribution shifts, or other types of biases. * Properties of ML methods/systems to be fulfilled to successfully deploy them in the clinic where the feasibility of these properties should also be taken into account. * Analyses of how to assess the failure modes of ML models for healthcare and reduce over-reliance. * Developing methods for improved interpretability of ML predictions in the context of healthcare. * Translational and implementational aspects: challenges and lessons learned from integrating an ML system into clinical workflow. More information can be found on our website: https://sites.google.com/g.harvard.edu/research2clinics/home Important dates: * Submissions Deadline: Sept 17, 2021 11:59 AoE * Authors Notification: Oct 16, 2021 11:59 AoE Organizers: Julia Vogt (ETH Zurich) Ece ?zkan (ETH Zurich) Sonali Parbhoo (Harvard University) Jiayu Yao (Harvard University) Shengpu Tang (University of Michigan) Melanie F. Pradier (MSR) Patrick Schwab (GSK) Mario Wieser (Genedata AG) -------------- next part -------------- An HTML attachment was scrubbed... URL: From odobez at idiap.ch Wed Aug 11 11:17:22 2021 From: odobez at idiap.ch (Jean-Marc Odobez) Date: Wed, 11 Aug 2021 17:17:22 +0200 Subject: Connectionists: [job] Idiap/EPFL (Switzerland): 1 PhD positions in multimodal gesture, visual attention an interaction activity recognition for autism diagnosis Message-ID: <3B5AAB8F-0930-4390-B14F-6E3C3521E29F@idiap.ch> Dear Colleagues, The Perception and Activity Understanding group (Jean-Marc Odobez, http://www.idiap.ch/~odobez/ ) seeks one highly motivated PhD candidate to work within the AI4Autism project aiming at improving the digital phenotyping of children with Autistic Spectrum Disorders (ASD). The PhD candidate will work on the multimodal perception of small children involved in free play activities as well as their social interactions with adults. In particular, he will investigate deep learning methods and models for the recognition of gestures and visual attention events, including the modeling of their coordination, from visual data and IoT sensors. Experiments will be conducted on various project data (e.g. data coming from standard ADOS evaluation protocol of more than 300 toddlers with partial behavior annotations) as well as standard datasets from the computer vision and multimodal domains (for gesture recognition, attention). The ideal PhD candidate should hold a MS degree in computer science, engineering, physics or applied mathematics. S/he should have a good background in statistics, linear algebra, signal processing and programming, machine learning. Experience in computer vision and deep learning are definitely a plus. The successful applicant will have good analytical skills, written and oral communication skills. The position is for 4 years, provided successful progress, and should lead to a dissertation. The selected candidates will become doctoral students at EPFL provided acceptance by the Doctoral School at EPFL (http://phd.epfl.ch/applicants ). Starting date is ideally on the 1st of November 2021. The salary follows the EPFL standards (52,400 annual gross salary in the first year). Interested candidates should submit a cover letter, a detailed CV, and the names of three references (or recommendation letters) through the Idiap online recruitment system: http://www.idiap.ch/job-opportunities . Interviews will start upon reception of applications until the position is filled. --- About the AI4Autism project and the PhD position. AI4Autism is a sinergia project funded by the SNSF and involving the University of Geneva (Marie Schaer , as well as Thomas Maillart ), the Human behavioral analysis research unit at the DTI department of the University of Applied Sciences and Arts of Southern Switzerland (SUPSI) (Michela Papandrea ), and the Perception and Activity Understanding group (Jean-Marc Odobez, http://www.idiap.ch/~odobez/ ) at the Idiap Research Institute (http://www.idiap.ch ). Project description: Nowadays, 1 in 59 children diagnosed with autism spectrum disorders (ASD), which makes this condition one of the most prevalent neurodevelopmental disorders. The AI4Autism project is grounded on the recognition that, on the one hand, early diagnosis at scale of autism in young children requires the development of tools for digital phenotyping and automated screening, through digital computer vision and Internet of Things sensing. On the other hand, it aims to examine the potential of digital sensing to provide automated measures of the extended and more fine-grained autism phenotypes. To address these two questions, the project proposes an interdisciplinary project combining the skills of experts in clinical research, engineering and computational social sciences to develop precise and scaled approaches for autism screening and profiling, by investigating three following research directions which are critical to move beyond the state-of-the-art. (1) Clinical research in autism: we propose a comprehensive and reproducible research approach designed to propose groundbreaking digital tools for screening and automated profiling of autism phenotype. It relies on the investigation of both a structured and well established protocol and a less structured one (free play) which may scale better. (2) Internet of Things (IoT): exploring the hypothesis that some ASD phenotypes might be related to the motor skills of very young children, we will explore the use IoT sensors for ASD diagnosis. (3) Computational perception and machine learning. The project will be rooted in modern AI, investigating novel machine learning and computer vision techniques leveraging the availability of large behavioral and clinical annotation data to propose novel behavioral cues extraction models working in challenging sensing conditions. PhD position: the Phd student will join a team of one PhD student and a postdoc at Idiap working on the project. He will work with them and study methods and models (domain adaptation, unsupervised or weakly supervised learning; temporal graph neural networks, attention-based neural networks and transformers) for the analysis of motor (recognizing gestures) and gaze coordination patterns which are at the core of ASD based on computer vision and IoT sensors, and investigate multimodal interaction deep-learning techniques for ASD diagnosis and profiling with a focus towards interpretable models. -- Jean-Marc Odobez, IDIAP Senior Researcher, Head of the Perception and Activity Understanding group EPFL Senior Researcher (EPFL MER) IDIAP Research Institute (http://www.idiap.ch) Tel: +41 (0)27 721 77 26 Web: http://www.idiap.ch/~odobez -------------- next part -------------- An HTML attachment was scrubbed... URL: From sepand.haghighi at yahoo.com Wed Aug 11 10:25:55 2021 From: sepand.haghighi at yahoo.com (Sepand Haghighi) Date: Wed, 11 Aug 2021 14:25:55 +0000 (UTC) Subject: Connectionists: PyCM 3.2 released: Machine learning library for confusion matrix statistical analysis References: <850226768.874609.1628691955705.ref@mail.yahoo.com> Message-ID: <850226768.874609.1628691955705@mail.yahoo.com> https://github.com/sepandhaghighi/pycm https://www.pycm.irhttp://list.pycm.ir - classes_filter?function added?#358 - classes?parameter added to?matrix_params_calc?function?#358 - classes?parameter added to?__obj_vector_handler__?function?#358 - classes?parameter added to ConfusionMatrix?__init__?method?#358 - name?parameter removed from?html_init?function - shortener?parameter added to?html_table?function?#364 - shortener?parameter added to?save_html?method?#364 - Document modified - HTML report modified Best RegardsSepand Haghighi -------------- next part -------------- An HTML attachment was scrubbed... URL: From massimo.srt at gmail.com Wed Aug 11 16:09:08 2021 From: massimo.srt at gmail.com (Massimo Sartori) Date: Wed, 11 Aug 2021 22:09:08 +0200 Subject: Connectionists: [jobs] Two postdoc openings: modelling and control of bio-protective robots for injury prevention and movement rehabilitation across large temporal scales (University of Twente) In-Reply-To: References: Message-ID: Do you want to develop wearable robots for preventing musculoskeletal injuries in occupational settings, e.g., factory workers performing manual tasks? Do you want to understand how skeletal muscles change their biological structure in response to mechanical stimuli and how rehabilitation robots (e.g., exoskeletons, robotic dynamometers) can steer such structural changes over time? The Neuro-Mechanical Modeling and Engineering Lab (Department of Biomechanical Engineering, University of Twente) is seeking for two outstanding postdoctoral fellows to work on two large-scale European projects respectively: - H2020 ERC project INTERACT: https://cordis.europa.eu/project/id/803035 - H2020 RIA project SOPHIA: https://project-sophia.eu *Please, apply via the links below:* - *Postdoc opening 1 (INTERACT project): Modeling skeletal muscle adaptation for the control of rehabilitation robots across large temporal scales: Apply here: https://www.utwente.nl/en/organisation/careers/!/128/ by September 13, 2021. * - *Postdoc opening 2 (SOPHIA project): Computational models of musculoskeletal injury prediction and control of bio-protective exosuits: Apply here: https://www.utwente.nl/en/organisation/careers/!/127/ by August 31, 2021. * We offer high-reaching positions with a generous allowance as well as extraordinary research facilities and working environment. Your work will be facilitated by in-house expertise and mentorship. You will collaborate with top-scientists on aspects including exoskeleton control, skeletal muscle modelling, statistical modelling, giving large opportunity of growth and to perform impactful research! The INTERACT Project aims to develop predictive models of the neuromuscular system to establish new closed-loop control methods for robotics-based neuro-rehabilitation. With a focus on spinal cord electrical stimulation and robotic exoskeleton, we will demonstrate how motor dysfunction is repaired by inducing optimal changes in neuromuscular targets. - Project Page: https://cordis.europa.eu/project/id/803035 The SOPHIA Project seeks to realize adaptable and safe human-robot collaborative environments. Through well-tested sensing methods, modeling, and control algorithms, SOPHIA will see humans and robots working together in factory production settings. In this way, SOPHIA will remove the separation between man and machine to improve factory output. SOPHIA consortium encompasses a large international consortium of academic and industrial partners. - Project Page: https://project-sophia.eu The Neuro-Mechanical Modelling & Engineering Lab. We interface robotic technologies with the neuromuscular system to improve movement. We apply modelling and signal processing, in a translational way, to develop novel real-time bio-inspired assistive technologies. Our goal is to establish a roadmap for discovering fundamental principles of movement at the interface between humans and wearable robots ultimately for improving human health. Check out our pages: - Lab: https://bit.ly/NMLab - YouTube: https://bit.ly/NMLTube The University of Twente. We stand for life sciences and technology. High tech and human touch. Education and research that matter. New technology which leads change, innovation and progress in society. We have a strong focus on personal development and talented researchers are given scope for carrying out groundbreaking research (https://www.utwente.nl/en/). --- Massimo Sartori, Ph.D. Associate Professor Director, Neuromechanical Modeling & Engineering Lab University of Twente TechMed Centre Department of Biomechanical Engineering 7500 AE, The Netherlands Personal Website: https://people.utwente.nl/m.sartori Lab Website: https://bit.ly/NMLab Lab YouTube Channel: https://bit.ly/NMLTube -------------- next part -------------- An HTML attachment was scrubbed... URL: From hocine.cherifi at gmail.com Wed Aug 11 05:22:57 2021 From: hocine.cherifi at gmail.com (Hocine Cherifi) Date: Wed, 11 Aug 2021 11:22:57 +0200 Subject: Connectionists: CFP COMPLEX NETWORKS 2021| Hybrid | Submission deadline: 01 Sep 2021 Message-ID: *10th** International Conference on Complex Networks & Their Applications* *Hybrid- Madrid, Spain *November 30 - December 02, 2021 COMPLEX NETWORKS 2021 You are cordially invited to submit your contribution until September 01, 2021. *SPEAKERS * ? Marc Barth?l?my CEA France ? Ginestra Bianconi Queen Mary University of London UK ? Jo?o Gama University of Porto Portugal ? Dirk Helbing ETH Z?rich Switzerland ? Yizhou Sun UCLA USA ? Alessandro Vespignani Northeastern University USA *TUTORIALS (November 29, 2021)* ? Elisabeth Lex Graz University of Technology Austria ? Giovanni Petri ISI Foundation Italy *PUBLICATION* Full papers (not previously published up to 12 pages) and Extended Abstracts (about published or unpublished research up to 3 pages) are welcome. ? *Papers *will be included in the conference *proceedings edited by Springer* ? *Extended abstracts* will be published in the *Book of Abstracts (with ISBN)* Templates are available on the submission webpage. If in doubt, please contact the Publication Chair (matteo.zignani at unimi.it) All contributions should be submitted via EasyChair . Extended versions will be invited for publication in *special issues of international journals:* o Applied Network Science edited by Springer o Complex Systems o Computational Social Networks edited by Springer o Network Science edited by Cambridge University Press o PLOS one o Social Network Analysis and Mining edited by Springer *TOPICS* *Topics include, but are not limited to: * o Models of Complex Networks o Structural Network Properties and Analysis o Complex Networks and Epidemics o Community Structure in Networks o Community Discovery in Complex Networks o Motif Discovery in Complex Networks o Network Mining o Network embedding methods o Machine learning with graphs o Dynamics and Evolution Patterns of Complex Networks o Link Prediction o Multilayer Networks o Network Controllability o Synchronization in Networks o Visual Representation of Complex Networks o Large-scale Graph Analytics o Social Reputation, Influence, and Trust o Information Spreading in Social Media o Rumour and Viral Marketing in Social Networks o Recommendation Systems and Complex Networks o Financial and Economic Networks o Complex Networks and Mobility o Biological and Technological Networks o Mobile call Networks o Bioinformatics and Earth Sciences Applications o Resilience and Robustness of Complex Networks o Complex Networks for Physical Infrastructures o Complex Networks, Smart Cities and Smart Grids o Political networks o Supply chain networks o Complex networks and information systems o Complex networks and CPS/IoT o Graph signal processing o Cognitive Network Science o Network Medicine o Network Neuroscience o Quantifying success through network analysis o Temporal and spatial networks o Historical Networks *GENERAL CHAIRS* Rosa Maria Benito *Universidad Politecnica de Madrid, Spain* Hocine Cherifi *University of Burgundy, France* Esteban Moro *Universidad Carlos III de Madrid, Spain* *ADVISORY BOARD* Jon Crowcroft *University of Cambridge, UK* Raissa D'Souza *UC Davis, USA* Eugene Stanley *Boston University, USA* Ben Y. Zhao *University of Chicago, USA* *PROGRAM CHAIRS* Chantal Cherifi *University of Lyon, France* Luis M. Rocha *Indiana University, USA* Marta Sales-Pardo *Universitat Rovira i Virgili, Spain* *LIGHTNING CHAIRS* Jes?s Gomez Garde?es *University of Zaragoza, Spain* Regino Criado* Universidad Rey Juan Carlos de Madrid, Spain* Huijuan Wang *TU Delft, Netherlands* *POSTER CHAIRS* Manuel Marques Pita *Universidade Lus?fona, Portugal* Taha Yasseri *University of Oxford, UK* Jos? Javier Ramasco *IFISC, Spain* *TUTORIAL CHAIRS* Luca Maria Aiello *Nokia-Bell Labs, UK* Leto Peel *Universit? Catholique de Louvain, Belgium* *SATELLITE CHAIR* Javier Galeano *Universidad Politecnica de Madrid, Spain* *PUBLICITY CHAIRS* Benjamin Renoust *Osaka University, Japan* Xiangjie Kong* Dalian* *University of Technology, China* *SPONSOR CHAIR* Roberto Interdonato *CIRAD, France* *STUDENT GRANT CHAIR* Sabrina Gaito *Universit? degli Studi di Milano, Italy* *PUBLICATION CHAIR* Matteo Zignani *Universit? degli Studi di Milano, Italy* *WEB CHAIR* Stephany Rajeh *University of Burgundy, France* *LOCAL COMMITTEE CHAIR* Juan Carlos Losada *Universidad Politecnica de Madrid, Spain* Join us at COMPLEX NETWORKS 2021 Madrid Spain *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comt? Deputy Director LIB EA N? 7534 Editor in Chief Applied Network Science Editorial Board member PLOS One , IEEE ACCESS , Scientific Reports , Journal of Imaging , Quality and Quantity , Computational Social Networks , Complex Systems Complexity -------------- next part -------------- An HTML attachment was scrubbed... URL: From Michael.Fauth at phys.uni-goettingen.de Thu Aug 12 05:21:52 2021 From: Michael.Fauth at phys.uni-goettingen.de (Fauth, Michael) Date: Thu, 12 Aug 2021 09:21:52 +0000 Subject: Connectionists: PhD in Goettingen: Molecular Mechanims of synaptic plasticity and consolidation Message-ID: <7bedab392255431e8d14646c127ccb71@phys.uni-goettingen.de> Apologies for cross-postings. The Institute of Biophysics at the Georg-August-Universit?t G?ttingen is looking to fill a Ph.D. position (German Salary Scale TV-L E13, 66% of 39.8 weekly hours) for 3 years to work on theoretical models of the molecular underpinnings of (structural) synaptic plasticity and consolidation. This post is designed to foster young researchers and give the successful applicant the opportunity to pursue a doctoral degree. The position should be filled by September 15th 2021 or soon thereafter. Suitable candidates should hold a Master in Physics, Mathematics, Computer Science or comparable subjects, preferably with some additional experiences in Computational Neuroscience, Geometrical Modeling and Stochastic Processes. We expect excellent mathematical and coding skills (e.g., Python, Matlab, C++) as well as skills in scientific communication (including proficiency in English). The candidate should be curious, highly motivated, self-organized, and show a keen interest to work in a lively research team, collaborate with experimental research labs and to perform leading-edge research. The positions will be affiliated with the groups of Dr. Michael Fauth and Prof Florentin W?rg?tter, who are investigating the emergence of stable behavior like memory and computation in the presence of a continuously changing biological substrate (see, e.g., Fauth & van Rossum, eLife, 2019; Bonilla-Quintana et al., Scientific Reports 2021). The aim of the research project is to model the dynamics of the synaptic scaffolding protein actin as well as its influence on synapse geometry during and after synaptic plasticity, exploring a possible molecular mechanism for the consolidation of synaptic changes. The project is embedded in and funded through the Collaborative Research Center 1286 ?Quantitative Synaptology? (German Science Foundation). Consequently, the successful candidate will also be involved and pursue an active collaboration with experimental partners within the CRC. The G?ttingen Campus is a leading center of neuroscience in Europe hosting numerous internationally renowned research institutions, including the University and its Medical Center, the three life science Max Planck Institutes, the European Neuroscience Institute, the German Primate Center, and the Bernstein Center for Computational Neuroscience (BCCN) G?ttingen. For more information, consult the official announcement at https://www.uni-goettingen.de/de/2794.html?cid=15701 From pubconference at gmail.com Wed Aug 11 08:40:09 2021 From: pubconference at gmail.com (Pub Conference) Date: Wed, 11 Aug 2021 08:40:09 -0400 Subject: Connectionists: KBS Special Issue on Deep Learning (IF: 8.038) Deadline: August 31, 2021 Message-ID: Robust, Explainable, and Privacy-Preserving Deep Learning https://www.journals.elsevier.com/knowledge-based-systems/call-for-papers/robust-explainable-and-privacy-preserving-deep-learning *Aim and Scope* The exponentially growing availability of data such as images, videos and speech from myriad sources, including social media and the Internet of Things, is driving the demand for high-performance data analysis algorithms. Deep learning is currently an extremely active research area in machine learning and pattern recognition. It provides computational models of multiple nonlinear processing neural network layers to learn and represent data with increasing levels of abstraction. Deep neural networks are able to implicitly capture intricate structures of large-scale data and deploy in cloud computing and high-performance computing platforms. The deep learning approach has demonstrated remarkable performances across a range of applications, including computer vision, image classification, face/speech recognition, natural language processing, and medical communications. However, deep neural networks yield ?black-box? input-output mappings that can be challenging to explain to users. Especially in the healthcare, cybersecurity, and legal fields, black-box machine learning techniques are unacceptable, since decisions may have a profound impact on peoples? lives due to the lack of interpretability. In addition, many other open problems and challenges still exist, such as computational and time costs, repeatability of the results, convergence, and the ability to learn from a very small amount of data and to evolve dynamically. Further, despite their enormous societal benefits, deep learning can pose real threats to personal privacy. For example, deep neural networks and other machine learning models are built based on patients' personal and highly sensitive data such as clinical records or tracked health data in the domain of healthcare. Moreover, they can be vulnerable to attackers trying to infer the sensitive data that was used to build the model. This raises important research questions about how to develop deep learning models that protect private data against inference attacks while still being accurate and useful predictive models. This Special Issue will present robust, explainable, and efficient next-generation deep learning algorithms with data privacy and theoretical guarantees for solving challenging artificial intelligence problems. This Special Issue aims to: 1) improve the understanding and explainability of deep neural networks; 2) improve the accuracy of deep learning leveraging new stochastic optimization and neural architecture search; 3) enhance the mathematical foundation of deep neural networks; 4) design new data privacy mechanisms to optimally tradeoff between utility and privacy; and 5) increase the computational efficiency and stability of the deep learning training process with new algorithms that will scale. Potential topics include but are not limited to the following: ? Novel theoretical insights on the deep neural networks ? Exploration of post-hoc interpretation methods which can shed light on how deep learning models produce a specific prediction and generate a representation ? Investigation of interpretable models which aim to construct self-explanatory models and incorporate interpretability directly into the structure of a deep learning model ? Quantifying or visualizing the interpretability of deep neural networks ? Stability improvement of deep neural network optimization ? Optimization methods for deep learning ? Privacy preserving machine learning (e.g., federated machine learning, learning over encrypted data) ? Novel deep learning approaches in the applications of image/signal processing, business intelligence, games, healthcare, bioinformatics, and security *Important Dates* ? Submission Deadline: August 31, 2021 ? First Review Decision: September 30, 2021 ? Revisions Due: October 31, 2021 ? Final Decision: November 30, 2021 ? Final Manuscript: December 31, 2021 *Review Procedures* This special issue will run as per the timeline given from submission to publication, while maintaining the rigorous peer review and high standards of the journal. All manuscripts submitted must be original, not under consideration elsewhere, and not previously published. A guide for authors and other relevant information for submission of manuscripts are available on the Guide for Authors? page. Authors can expect their manuscripts to be reviewed fairly, and in a skilled, conscientious manner. To enhance objectivity, and to guarantee high scientific quality and relevance to the subject, three peer reviewers will be selected to evaluate a manuscript. The peer review process shall be designed to avoid bias and conflict of interest on the part of reviewers and shall be composed of experts in the relevant field of research. A key criterion in publication decisions will be the manuscript?s fit for the special issue and the readership of KBS. Papers will be published online as soon as accepted in continuous flow. *Submission Instructions* The submission system will be open around one week before the first paper comes in. When submitting your manuscript please select the article type ?*VSI: Deep Learning*?. Please submit your manuscript before the submission deadline. All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles. Please see an example here: https://www.sciencedirect.com/journal/science-of-the-total-environment/special-issue/10SWS2W7VVV Please ensure you read the Guide for Authors before writing your manuscript. The Guide for Authors and the link to submit your manuscript is available on the Journal?s homepage. -------------- next part -------------- An HTML attachment was scrubbed... URL: From samuel.kaski at aalto.fi Wed Aug 11 12:04:33 2021 From: samuel.kaski at aalto.fi (Kaski Samuel) Date: Wed, 11 Aug 2021 16:04:33 +0000 Subject: Connectionists: Research Fellows and Postdocs in Probabilistic Machine Learning and Bayesian Inference Message-ID: <3C016AD4-4258-404A-B642-6E8BCC0D1445@aalto.fi> Research Fellows and Postdocs in Probabilistic Machine Learning and Bayesian Inference I am looking for researchers to my new team in Manchester, UK, funded by the UKRI Turing AI World-Leading Researcher Fellowship programme "Human-AI Research Teams - Steering AI in Experimental Design and Decision-Making". Closing date of call: September 6, 2021. The research is fundamental research in probabilistic modelling and Bayesian inference, applied to the exciting problems of how do we steer machine learning systems. Particularly challenging is to steer when we cannot (yet) precisely specify our goal, and ultimately we would like to have machine learning systems that help us in experimental design and decisions. Keywords include: advanced user modelling, automatic experimental design, Bayesian inference, human-in-the-loop learning, machine teaching, privacy-preserving learning, reinforcement learning and inverse reinforcement learning with or without multiple agents, and simulator-based inference. I am not expecting anyone to master all of these, though if you do, please apply immediately... The team will have excellent opportunities of applying the methods to medicine, especially cancer research and remote medicine; experimental design in synthetic biology and drug design; and digital twins. We have top-notch collaborators in each, both in Academia and in companies, locally and internationally. We can also discuss jointly funded positions with partner companies, hospitals or collaborator groups. More info about these fellowships and my research programme: https://www.ukri.org/news/global-leaders-named-as-turing-ai-world-leading-researcher-fellows/ https://www.manchester.ac.uk/discover/news/new-human-ai-research-teams-could-be-the-future-of-research-meeting-future-societal-challenges/ More info about these positions and a link to the application portal: Research fellows: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=20643 , DL September 6, 2021 Postdocs: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=20642 , DL September 12, 2021 Lastly: why Manchester? 1. Because we are there 2. Great university, with fluent collaboration with outstanding groups of application fields 3. It is the place to be right now for machine learning. New Fundamental AI Research Centre with several new academics is being launched, on top of the already wide AI activity including Turing Institute partnership with 27 Turing Fellows and ELLIS Fellows. 4. The most livable city in the UK (https://www.investinmanchester.com/why-manchester/living-in-manchester/quality-of-life) Best wishes, Samuel Kaski samuel.kaski at manchester.ac.uk https://www.research.manchester.ac.uk/portal/samuel.kaski.html From massimo.srt at gmail.com Wed Aug 11 16:09:08 2021 From: massimo.srt at gmail.com (Massimo Sartori) Date: Wed, 11 Aug 2021 22:09:08 +0200 Subject: Connectionists: [jobs] Two postdoc openings: modelling and control of bio-protective robots for injury prevention and movement rehabilitation across large temporal scales (University of Twente) In-Reply-To: References: Message-ID: Do you want to develop wearable robots for preventing musculoskeletal injuries in occupational settings, e.g., factory workers performing manual tasks? Do you want to understand how skeletal muscles change their biological structure in response to mechanical stimuli and how rehabilitation robots (e.g., exoskeletons, robotic dynamometers) can steer such structural changes over time? The Neuro-Mechanical Modeling and Engineering Lab (Department of Biomechanical Engineering, University of Twente) is seeking for two outstanding postdoctoral fellows to work on two large-scale European projects respectively: - H2020 ERC project INTERACT: https://cordis.europa.eu/project/id/803035 - H2020 RIA project SOPHIA: https://project-sophia.eu *Please, apply via the links below:* - *Postdoc opening 1 (INTERACT project): Modeling skeletal muscle adaptation for the control of rehabilitation robots across large temporal scales: Apply here: https://www.utwente.nl/en/organisation/careers/!/128/ by September 13, 2021. * - *Postdoc opening 2 (SOPHIA project): Computational models of musculoskeletal injury prediction and control of bio-protective exosuits: Apply here: https://www.utwente.nl/en/organisation/careers/!/127/ by August 31, 2021. * We offer high-reaching positions with a generous allowance as well as extraordinary research facilities and working environment. Your work will be facilitated by in-house expertise and mentorship. You will collaborate with top-scientists on aspects including exoskeleton control, skeletal muscle modelling, statistical modelling, giving large opportunity of growth and to perform impactful research! The INTERACT Project aims to develop predictive models of the neuromuscular system to establish new closed-loop control methods for robotics-based neuro-rehabilitation. With a focus on spinal cord electrical stimulation and robotic exoskeleton, we will demonstrate how motor dysfunction is repaired by inducing optimal changes in neuromuscular targets. - Project Page: https://cordis.europa.eu/project/id/803035 The SOPHIA Project seeks to realize adaptable and safe human-robot collaborative environments. Through well-tested sensing methods, modeling, and control algorithms, SOPHIA will see humans and robots working together in factory production settings. In this way, SOPHIA will remove the separation between man and machine to improve factory output. SOPHIA consortium encompasses a large international consortium of academic and industrial partners. - Project Page: https://project-sophia.eu The Neuro-Mechanical Modelling & Engineering Lab. We interface robotic technologies with the neuromuscular system to improve movement. We apply modelling and signal processing, in a translational way, to develop novel real-time bio-inspired assistive technologies. Our goal is to establish a roadmap for discovering fundamental principles of movement at the interface between humans and wearable robots ultimately for improving human health. Check out our pages: - Lab: https://bit.ly/NMLab - YouTube: https://bit.ly/NMLTube The University of Twente. We stand for life sciences and technology. High tech and human touch. Education and research that matter. New technology which leads change, innovation and progress in society. We have a strong focus on personal development and talented researchers are given scope for carrying out groundbreaking research (https://www.utwente.nl/en/). --- Massimo Sartori, Ph.D. Associate Professor Director, Neuromechanical Modeling & Engineering Lab University of Twente TechMed Centre Department of Biomechanical Engineering 7500 AE, The Netherlands Personal Website: https://people.utwente.nl/m.sartori Lab Website: https://bit.ly/NMLab Lab YouTube Channel: https://bit.ly/NMLTube -------------- next part -------------- An HTML attachment was scrubbed... URL: From zhangdingwen2006yyy at gmail.com Thu Aug 12 00:10:35 2021 From: zhangdingwen2006yyy at gmail.com (Dingwen Zhang) Date: Thu, 12 Aug 2021 12:10:35 +0800 Subject: Connectionists: [journals] CFP: TMM SI, submission deadline approaching (8.15) Message-ID: 3-day deadline for the upcoming special issue on IEEE T-MM.More detailed dates and scope of the special issue are listed below. Looking forward to your contribution! *SUMMARY:* With the goal of addressing fine-level image and video understanding tasks by learning from coarse-level human annotations, WSL is of particular importance in such a big data era as it can dramatically alleviate the human labor for annotating each of the structured visual/multimedia data and thus enables machines to learn from much larger-scaled data but with the equal annotation cost of the conventional fully supervised learning methods. More importantly, when dealing with the data from real-world application scenarios, such as the medical imaging data, remote sensing data, and audio-visual data, fine-level manual annotations are very limited and difficult to obtain. Under these circumstances, the WSL-based learning frameworks, specifically for the WSL-based multi-modality/multi-task learning frameworks, would bring great benefits. Unfortunately, designing effective WSL systems is challenging due to the issues of ?semantic unspecificity? and ?instance ambiguity?, where the former refers to the setting where the provided semantic label is at image level rather than specific instance-level while the latter refers to the ambiguity when determining an instance sample against the instance part or instance cluster. Principled solutions to address these problems are still under-studied. Nowadays, with the rapid development of advanced machine learning techniques, such as the Graph Convolutional Networks, Capsule Networks, Transformers, Generative Adversarial Networks, and Deep Reinforcement Learning models, new opportunities have emerged for solving the problems in WSL and applying WSL to richer vision and multimedia tasks. This special issue aims at promoting cutting-edge research along this direction and offers a timely collection of works to benefit researchers and practitioners. We welcome high-quality original submissions addressing both novel theoretical and practical aspects related to WSL, as well as the real-world applications based on WSL approaches. *SCOPE:* Topics of interests include, but are not limited to: - Multi-modality weakly supervised learning theory and framework; - Multi-task weakly supervised learning theory and framework; - Robust learning theory and framework; - Audio-visual learning under weak supervision; - Weakly supervised spatial/temporal feature learning; - Self-supervised learning frameworks and applications; - Graph Convolutional Networks/Graph Neural Networks-based weakly supervised learning frameworks; - Deep Reinforcement Learning for weakly supervised learning; - Emerging vision and multimedia tasks with limited supervision; *IMPORTANT DATESs: * Manuscript submission: 15th August 2021 Preliminary results: 15th November 2021 Revisions due: 1st January 2022 Notification: 15th February 2022 Final manuscripts due: 15th March 2022 Anticipated publication: Midyear 2022 *SUBMISSION PROCEDURE:* Papers should be formatted according to the IEEE Transactions on Multimedia guidelines for authors (see: http://www.signalprocessingsociety.org/tmm/tmm-author-info/). By submitting/resubmitting your manuscript to these Transactions, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay all over-length page charges, color charges, and any other charges and fees associated with publication of the manuscript. Manuscripts (both 1-column and 2-column versions are required) should be submitted electronically through the online IEEE manuscript submission system at http://mc.manuscriptcentral.com/tmm-ieee. All submitted papers will go through the same review process as the regular TMM paper submissions. Referees will consider originality, significance, technical soundness, clarity of exposition, and relevance to the special issue topics above. -- Dingwen Zhang https://zdw-nwpu.github.io/dingwenz.github.com/ Northwestern Polytechnical University -------------- next part -------------- An HTML attachment was scrubbed... URL: From Bing.Xue at ecs.vuw.ac.nz Wed Aug 11 17:47:11 2021 From: Bing.Xue at ecs.vuw.ac.nz (Bing XUE) Date: Thu, 12 Aug 2021 09:47:11 +1200 Subject: Connectionists: 2nd CFP EuroGP 2022 - 25th European Conference on Genetic Programming - 20-22 April 2022 In-Reply-To: <244ab843-cfd0-404d-0d13-f38965d2c58d@ecs.vuw.ac.nz> References: <244ab843-cfd0-404d-0d13-f38965d2c58d@ecs.vuw.ac.nz> Message-ID: <736d5200-d348-b978-0af7-b11226515755@ecs.vuw.ac.nz> Dear Colleague(s), *** Apologies for cross-posting *** We would like to invite you to submit papers to EuroGP 2022: THE 25th EUROPEAN CONFERENCE ON GENETIC PROGRAMMING which will be held on April 20-22, 2022 Please visit http://www.evostar.org for more details. *** Important dates *** Submission deadline: 1 November 2021 EvoStar Conference: 20-22 April, 2022 *** EuroGP *** EuroGP is the premier annual conference on Genetic Programming (GP), the oldest and the only meeting worldwide devoted specifically to this branch of evolutionary computation. It is always a high-quality, enjoyable, friendly event, attracting participants from all continents, and offering excellent opportunities for networking, informal contact, and exchange of ideas with fellow researchers. It will feature a mixture of oral presentations and poster sessions and invited keynote speakers. EuroGP is featured in the conference ranking database CORE (http://portal.core.edu.au/conf-ranks/481/) *** EvoStar *** EvoStar is a leading international event devoted to evolutionary computing, comprising four conferences, EuroGP, EvoApplications, EvoCOP, and EvoMUSART. The low-cost registration includes access to all of them, as well as daily lunch and the conference reception and banquet. *** Topics *** Topics to be covered include, but are not limited to: Innovative applications of GP, Theoretical developments, GP performance and behaviour, Fitness landscape analysis of GP, Algorithms, representations and operators for GP, Search-based software engineering, Genetic improvement programming, Evolutionary design, Evolutionary robotics, Tree-based GP and Linear GP, Graph-based GP and Grammar-based GP, Evolvable hardware, Self-reproducing programs, Multi-population GP, Multi-objective GP, Parallel GP, Probabilistic GP, Object-orientated GP, Hybrid architectures including GP, Coevolution and modularity in GP, Semantics in GP, Unconventional GP, Automatic software maintenance, Evolutionary inductive programming, Evolution of automata or machines. ***the EvoML joint track *** Please visit: http://www.evostar.org/2022/eml/ This joint track on Evolutionary Machine Learning (EML) will provide a specialized forum of discussion and exchange of information for researchers interested in exploring approaches that combine nature and nurture, with the long-term goal of evolving Artificial Intelligence (AI). In response to the growing interest in the area, and consequent advances of the state-of-the-art, the special session covers theoretical and practical advances on the combination of Evolutionary Computation (EC) and Machine Learning (ML) techniques. As a joint EuroGP+EvoAPPS track, authors should decide whether their paper will be treated within EvoApplications or EuroGP at the submission time. *** Paper submission *** High-quality submissions not exceeding 16 pages in Springer LNCS format are now solicited. Accepted papers will be published by Springer-Verlag in the Lecture Notes in Computer Science series. The highest quality papers may also be invited to submit extensions for publication in a special issue of the journal Genetic Programming and Evolvable Machines (GPEM). *** Organization *** Program Chairs: Eric Medvet, University of Trieste, Italy Gisele Pappa, Universidade Federal de Minas Gerais, Brazil Publication Chair: Bing Xue, Victoria University of Wellington *** Program Committee *** (To be announced) For further information please visit http://www.evostar.org. Eric Medvet, Gisele Pappa, and Bing Xue EuroGP Chairs -- ---------------------------------------------- Dr Bing Xue (she/her), MIEEE, MACM Professor | Ahorangi Programme Director of Science | Pouakorangi School of Engineering and Computer Science | Te Kura M?tai P?kaha, P?rorohiko Victoria University of Wellington | Te Herenga Waka New Zealand | Aotearoa Phone: +64 4 463 5542 Homepage: https://homepages.ecs.vuw.ac.nz/~xuebing/index.html ---------------------------------------------- From dftschool at ini.rub.de Wed Aug 11 08:11:45 2021 From: dftschool at ini.rub.de (DFT Summer School) Date: Wed, 11 Aug 2021 14:11:45 +0200 Subject: Connectionists: Neuronal Dynamics for Embodied Cognition - Virtual Summer School 2021. Application deadline extended to August 25! Message-ID: <86f9216e-3f7a-f3f0-14d3-f5c4221c8dc0@ini.rub.de> Please forward this advertisement to whoever you think might be interested. This virtual edition of our summer school will consist of two parts: An open-for-everyone live-lecture series and a hands-on workshop with a limited number of participants. We still have *open slots *in our workshop, so please consider joining us. The deadline for workshop applications has been extended to August 25, 2021! Participation in any part of the school is free of charge. Thanks, Raul Grieben and Jan Tek?lve --- Virtual DFT School 2021 This year our summer school "Neural Dynamics for Embodied Cognition" will take place in virtual form from the 6th to the 11th of September, 2021. Neuronal dynamics provide a powerful theoretical language for the design and modeling of embodied and situated cognitive systems. This school provides a hands-on and practical introduction to neuronal dynamics ideas and enables participants to become productive within this framework. The school is aimed at advanced undergraduate or graduate students, postdocs and faculty members in embodied cognition, cognitive science, and robotics. Topics addressed include neural dynamics, attractor dynamics and instabilities, dynamic field theory, neuronal representations, artificial perception, simple forms of cognition including detection and selection decisions, memory formation, learning, and grounding relational concepts. This virtual edition of our summer school will consist of two parts: A live-lecture series and a hands-on workshop. The lecture series will be held as a video conference and provides a step-by-step introduction to Dynamic Field Theory. The two-and-a-half-day project workshop gives students the opportunity to put to use the newly acquired skills in a concrete hands-on modeling project. Students solve the task in our open-source simulation environment under the guidance of a personal tutor. This year's lectures will be open for everyone,? while the one-on-one tutoring limits the number of participants who can take part in the workshop. We also encourage workshop applications by small groups of participants, maybe two or three colleagues who will work together locally on the same project and may share a tutor. Although this format will not retain the appeal of meeting other students in person, we will make this year's experience as interactive as possible. The lecture series will be held from the 6th to the 11th of September and the workshop takes place from the 9th to the 11th of September. Lectures will take place from 3 to 6 p.m. (CET) on each day and personal tutoring will be available on each workshop day. Participation in any part of the school is free of charge. To apply for the lecture series and/or the workshop, please visit our webpage: https://dynamicfieldtheory.org/events/summer_school_2021/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From O.Inel at tudelft.nl Fri Aug 13 03:49:55 2021 From: O.Inel at tudelft.nl (Oana Inel) Date: Fri, 13 Aug 2021 07:49:55 +0000 Subject: Connectionists: Call-for-Papers Special Issue "Explainable User Models" (Multimodal Technologies and Interaction Journal) Message-ID: <4312B844-D450-47F8-AA7E-6FB99DE61638@tudelft.nl> ? Apologies for cross-posting ? Special Issue "Explainable User Models" A special issue of Multimodal Technologies and Interaction (ISSN 2414-4088). Important Dates & Facts: Abstract/title submission: ideally until November 5, 2021 Manuscripts due by: February 20, 2022 Notification to authors: March 15, 2022 Website: https://www.mdpi.com/journal/mti/special_issues/Explainable_User_Models Special Issue Information This special issue addresses research on Explainable User Models. As AI systems? actions and decisions will significantly affect their users, it is important to be able to understand how an AI system represents its users. It is a well-known hurdle that many AI algorithms behave largely as black boxes. One key aim of explainability is, therefore, to make the inner workings of AI systems more accessible and transparent. Such explanations can be helpful in the case when the system uses information about the user to develop a working representation of the user, and then uses this representation to adjust or inform system behavior. E.g., an educational system could detect whether students have a more internal or external locus of control, a music recommender system could adapt the music it is playing to the current mood of a user, or an aviation system could detect the visual memory capacity of its pilots. However, when adapting to such user models it is crucial that these models are accurately detected. Furthermore, for such explanations to be useful, they need to be able to explain or justify their representations of users in a human-understandable way. This creates a necessity for techniques that will create models for the automatic generation of satisfactory explanations intelligible for human users interacting with the system. The scope of the special issue includes but is not limited to: Detection and Modelling ? Novel ways of Modeling User Preferences ? Types of information to model (Knowledge, Personality, Cognitive differences, etc.) ? Distinguishing between stationary versus transient user models (e.g., Personality vs Mood) ? Context modeling (e.g., at work versus at home, lean in versus lean out activities) ? User models from heterogeneous sources (e.g., behavior, ratings, and reviews) ? Enrichment and Crowdsourcing for Explainable User Models Ethics ? Detection of sensitive or rarely reported attributes (e.g., gender, race, sexial orientation) ? Implicit user modeling versus explicit user modeling (e.g., questionnaires versus inference from behavior) ? User modeling for self actualization (e.g., user modeling to improve dietary or news consumption habits) Human understandability ? Metrics and methodologies for evaluating fitness for the purpose of explanations ? Balancing completeness and understandability for complex user models ? Explanations to mitigate human biases (e.g., confirmation bias, anchoring) ? Effect of user model explanation on subsequent user interaction (e.g., simulations, and novel evaluation methodologies) Effectiveness ? Analysis or comparison of context of use of explanation (e.g., risk, time pressure, error tolerance) ? Analysis of context of use of system (e.g., decision support, prediction) ? Analysis or comparison of effect of explaining in specific domains (e.g., education, health, recruitment, security) Adaptive presentation of the explanations ? For different types of user ? Interactive explanations ? Investigation of which presentational aspects are beneficial to tailor in the explanation (e.g., level of detail, terminology, modality text or graphics, level of interaction) Prof. Dr. Nava Tintarev Ms. Oana Inel Guest Editors -------------- next part -------------- An HTML attachment was scrubbed... URL: From suashdeb at gmail.com Fri Aug 13 11:47:53 2021 From: suashdeb at gmail.com (Suash Deb) Date: Fri, 13 Aug 2021 21:17:53 +0530 Subject: Connectionists: abt ISMSI22 Message-ID: Hello friends & esteemed colleagues, Warmest greetings. Trust all of you are safe and doing well. Thanks once more for your patronage for the ISMSI 2022. With little more than 3 months left for submission of manuscripts, it may be appropriate to commence planning abt submission of your own papers http://ismsi.org/ I hope you will consider submission. At this juncture, we do hope to be able to organize ISMSI 2022 in face-to-face although we can't predict what would be the covid situation next year. Our present stand has been formally stated at the home page of the conference In addition, attached pls. find the PDF & txt version of the cfp for facilitating dissemination of the same among your peers & doctoral students, if appropriate. Stay safe & with warm rgds, Suash -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- 2022 6th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence ISMSI 2022 Seoul, Republic of Korea April 9-10, 2022 Website: http://www.ismsi.org All the accepted papers of ISMSI 2017-2021 have been published by ACM and indexed by EI, Scopus. Accepted Papers after registration and presentation at ISMSI 2022 will be published in International Conference Proceedings, which will be indexed by EI Compendex, Scopus, and submitted to be reviewed by Thomson Reuters (ISI Web of Science). European Journal of Operational Research, an Elsevier Publication [SCIE indexed, 2020 lmpact Factor : 5.334, 5 Year Impact Factor : 5.808 ], will consider for publication a few selected expanded papers of lSMSl22 in its usual reviewing process. A special issue of "Neural Computing & Applications", a Springer Publication [SCIE indexed, 2020 lmpact Factor : 5.606, 5 Year Impact Factor: 5.573; ISSN: 0941-0643 (print version) ISSN: 1433-3058 (electronic version)], will publish a selected set of extended versions of ISMSI22 papers (to be shortlisted after the conference), after the usual reviewing of those papers. Keynote Speakers: Prof. Panos M. Pardalos: University of Florida, USA Prof. Carlos A. Coello Coello: CINVESTAV-IPN, Mexico Prof. Ke Tang: Southern University of Science and Technology, Shenzhen, China Important Date: Submission Deadline November 20, 2021 Notification Date December 15, 2021 Registration Deadline January 5, 2022 Conference Dates April 9-10, 2022 Submission Method: https://www.easychair.org/conferences/?conf=ismsi2022 Contact Information: Nancy Liu (Conference Secretary) E-mail: sub at ismsi.org Tel: +86-13709044746 -------------- next part -------------- A non-text attachment was scrubbed... Name: Leaflet-ISMSI22.pdf Type: application/pdf Size: 411247 bytes Desc: not available URL: From heinrich.stefan at ircn.jp Sun Aug 15 08:56:34 2021 From: heinrich.stefan at ircn.jp (Stefan Heinrich) Date: Sun, 15 Aug 2021 21:56:34 +0900 Subject: Connectionists: Call For Participation - Workshop on Spatio-temporal Aspects of Embodied Predictive Processing - StEPP @ ICDL2021 - 22.08.2021 Message-ID: Call For Participation - Workshop on Spatio-temporal Aspects of Embodied Predictive Processing - StEPP @ IEEE ICDL2021 Schedule and Venue Date: 22. August 2021, 13:30-18:00h (GMT+8) Location: Online (Details will be announced on the website) All details and full schedule: https://sites.google.com/view/stepp21 Aims and Scope: Understanding human intelligence and building strong AI systems is a key challenge for our generation. A particularly puzzling aspect is that the human brain seems to cope very well with the highly variable and uncertain nature of perception and action, regarding both their signal characteristic and how they extend over time. Furthermore, it seems apparent that the information processing in the brain always involves previous bodily experiences and all our senses, thus is embodied and crossmodal. For explaining these characteristics, there are strong accounts that the brain is constantly predicting sensory input and feedback while minimising free energy in the prediction and is hierarchically abstracting the perception as well as hierarchically composing action. Furthermore, it is also hypothesised that mechanistic priors in the brain?s information processing induce a failure of hierarchical inference in the brain, accounting for atypical perception and action of psychiatric disorders. For example, some brains might have developed to focus too strongly on current sensory input while others might focus too strongly on memorised previous experience. A typically developed brain, in contrast, would show a fine balance compared to these two extreme priors. The big open mystery is: how is the brain developing this on a mechanistic level and thus how can this get learned within an AI system? Thus, to lift this mystery, we further need to bring together research from computational neuroscience, cognitive psychology, and artificial intelligence. With this workshop, we particularly want to wrap up different recent hypotheses, models, and experiments and discuss in-depth how to shape future imaging, behavioural, and developmental robotics studies as a complement to computational modelling and bio-inspired artificial intelligent algorithms. As a guiding theme, we aim to approach the following central questions: - How does the brain learn spatio-temporal stochasticity in perception and action? - What is the role of priors in learning spatio-temporal adaptive prediction? - How can developmental robotics help us to study spatio-temporal stochasticity as an analogy to infant learning? We examine these questions with the insight from invited key speakers from complementary fields as well as original contributions in breakout sessions in order to conclude the next steps within a panel discussion. Keynotes/Panellists and topics: - Jun Tani, Cognitive Neurorobotics, Okinawa Institute of Science and Technology (OIST) ? An analysis of meta-level cognitive processes of a variational recurrent neural network model when acting with the environment. - Marcel van Gerven, Artificial Cognitive Systems, Donders Institute, Radboud University ? How can the brain match the unreasonable effectiveness of backpropagation? - Takuya Isomura, Brain Intelligence Theory, RIKEN Center for Brain Science ? Reverse engineering Bayesian aspect of canonical neural networks. - Takamitsu Watanabe, Brain Network Dynamics, International Research Center for Neurointelligence (IRCN), The University of Tokyo ? Global and local brain dynamics underlying typical and atypical human intelligence. Organisers: Stefan Heinrich, IRCN, The University of Tokyo, Japan Shingo Murata, Dept. Electronics and Electrical Engineering, Keio University, Japan Yukie Nagai, IRCN & Institute for AI and Beyond, The University of Tokyo, Japan Yuichi Yamashita, National Center of Neurology and Psychiatry, Japan -- ************************************************************* Dr. Stefan Heinrich Postdoctoral Project Researcher Cognitive Developmental Robotics Lab The University of Tokyo, Institutes for Advanced Studies, International Research Center for Neurointelligence Email: heinrich.stefan at ircn.jp https://developmental-robotics.jp/en/members/stefan_heinrich/ https://ircn.jp/en/ https://stefanheinrich.net/ ************************************************************* -------------- next part -------------- A non-text attachment was scrubbed... Name: OpenPGP_0x3F7E078F1EF07893.asc Type: application/pgp-keys Size: 1769 bytes Desc: OpenPGP public key URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: OpenPGP_signature Type: application/pgp-signature Size: 495 bytes Desc: OpenPGP digital signature URL: From suashdeb at gmail.com Fri Aug 13 11:49:54 2021 From: suashdeb at gmail.com (Suash Deb) Date: Fri, 13 Aug 2021 21:19:54 +0530 Subject: Connectionists: abt ISMSI22 Message-ID: Hello friends & esteemed colleagues, Warmest greetings. Trust all of you are safe and doing well. Thanks once more for your patronage for the ISMSI 2022. With little more than 3 months left for submission of manuscripts, it may be appropriate to commence planning abt submission of your own papers http://ismsi.org/ I hope you will consider submission. At this juncture, we do hope to be able to organize ISMSI 2022 in face-to-face although we can't predict what would be the covid situation next year. Our present stand has been formally stated at the home page of the conference In addition, attached pls. find the PDF & txt version of the cfp for facilitating dissemination of the same among your peers & doctoral students, if appropriate. Stay safe & with warm rgds, Suash -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- 2022 6th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence ISMSI 2022 Seoul, Republic of Korea April 9-10, 2022 Website: http://www.ismsi.org All the accepted papers of ISMSI 2017-2021 have been published by ACM and indexed by EI, Scopus. Accepted Papers after registration and presentation at ISMSI 2022 will be published in International Conference Proceedings, which will be indexed by EI Compendex, Scopus, and submitted to be reviewed by Thomson Reuters (ISI Web of Science). European Journal of Operational Research, an Elsevier Publication [SCIE indexed, 2020 lmpact Factor : 5.334, 5 Year Impact Factor : 5.808 ], will consider for publication a few selected expanded papers of lSMSl22 in its usual reviewing process. A special issue of "Neural Computing & Applications", a Springer Publication [SCIE indexed, 2020 lmpact Factor : 5.606, 5 Year Impact Factor: 5.573; ISSN: 0941-0643 (print version) ISSN: 1433-3058 (electronic version)], will publish a selected set of extended versions of ISMSI22 papers (to be shortlisted after the conference), after the usual reviewing of those papers. Keynote Speakers: Prof. Panos M. Pardalos: University of Florida, USA Prof. Carlos A. Coello Coello: CINVESTAV-IPN, Mexico Prof. Ke Tang: Southern University of Science and Technology, Shenzhen, China Important Date: Submission Deadline November 20, 2021 Notification Date December 15, 2021 Registration Deadline January 5, 2022 Conference Dates April 9-10, 2022 Submission Method: https://www.easychair.org/conferences/?conf=ismsi2022 Contact Information: Nancy Liu (Conference Secretary) E-mail: sub at ismsi.org Tel: +86-13709044746 -------------- next part -------------- A non-text attachment was scrubbed... Name: Leaflet-ISMSI22.pdf Type: application/pdf Size: 411247 bytes Desc: not available URL: From xavier.hinaut at inria.fr Fri Aug 13 14:37:58 2021 From: xavier.hinaut at inria.fr (Xavier Hinaut) Date: Fri, 13 Aug 2021 20:37:58 +0200 Subject: Connectionists: 2nd SMILES workshop, Aug 31st: Sensorimotor Interaction, Language and Embodiment of Symbols Message-ID: * WHAT The SMILES workshop is about Sensorimotor Interaction, Language and Embodiment of Symbols (SMILES). It is a satellite event from the ICDL 2020 (International Conference on Developmental Learning). * WHEN Tuesday 31st of August 2021. Planned schedule (it might change): 9am - 8.30pm CEST (UTC+2). * WHERE Online event on Zoom. (Link sent to registered people the day before, see LINKS section) * WHO 8 Invited speakers from multiple fields: neurolinguistics, speech communication, language evolution, developmental science, social robotics, computational neuroscience, language acquisition. - Morten Christiansen, Cornell University, NY, USA & Aarhus University, Denmark - Kaya de Barbaro, University of California San Diego, USA - Cynthia Matuszek, University of Maryland, Baltimore County, USA - Yair Lakretz, NeuroSpin Center, Gif sur Yvette, France - Harm Brouwer, Saarland University, Germany - Jean-Luc Schwartz, Gipsa lab, Grenoble-Alpes University, France - Daniel Dor, Tel Aviv University, Israel - Lauren Emberson, University of British Columbia, Canada * LINKS - ** Website **: https://sites.google.com/view/smiles-workshop/home - ** Registration is free but mandatory **: https://forms.gle/tyvMdbb8UJFyXZky8 - Contact: smiles.conf at gmail.com - ICDL conference website: https://icdl-2021.org/ * WHAT+ (Short Description) On the one hand, models of sensorimotor interaction are embodied in the environment and in the interaction with other agents. On the other hand, recent Deep Learning development of Natural Language Processing (NLP) models allow to capture increasing language complexity (e.g. compositional representations, word embedding, long term dependencies). However, those NLP models are disembodied in the sense that they are learned from static datasets of text or speech. How can we bridge the gap from low-level sensorimotor interaction to high-level compositional symbolic communication? The SMILES workshop will address this issue through an interdisciplinary approach involving researchers from (but not limited to): - Sensori-motor learning, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Sensori-motor learning, - Symbol grounding and symbol emergence, - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and acquisition in brains and machines, - Models of animal communication, - Language evolution, - Understanding composition and temporal processing in neural network models, and - Enaction, active perception, perception-action loop. SMILES workshop organisers - Xavier Hinaut, Inria, Bordeaux, France - Cl?ment Moulin-Frier, Inria and Ensta ParisTech, Bordeaux, France - Silvia Pagliarini, Inria, Bordeaux, France - Michael Spranger, Sony AI and Sony CSL, Tokyo, Japan - Tadahiro Taniguchi, Ritsumeikan University, Kyoto, Japan - Anne S. Warlaumont, University of California, Los Angeles, America - Junpei Zhong, Nottingham Trent University, Nottingham, United Kingdom Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Universit? de Bordeaux Institut des Maladies Neurod?g?n?ratives www.xavierhinaut.com From bill.stine at unh.edu Mon Aug 16 10:27:17 2021 From: bill.stine at unh.edu (William Stine) Date: Mon, 16 Aug 2021 14:27:17 +0000 Subject: Connectionists: One-Year Lectureship in Cognitive Neuroscience Open for Fall '21 Message-ID: <65C08109-4C12-4D51-AC85-6704542D9E28@unh.edu> Apologies for cross-posting. Cognitive Neuroscience, Lecturer The Department of Psychology at the University of New Hampshire invites applications for a one-year, non-tenure-track lecturer position to begin fall, 2021, with a specialty in Cognitive Neuroscience. Area of specialization within Cognitive Neuroscience is open; however, the Department is particularly interested in individuals who are willing and able to teach Cognitive Neuroscience and the Neuroscience of Memory at the senior level, and Introduction to Statistics. The University of New Hampshire is an Equal Opportunity/Equal Access/Affirmative Action institution. The University seeks excellence through diversity among its administrators, faculty, staff, and students. The university prohibits discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, veteran status, or marital status. Application by members of all underrepresented groups is encouraged. Requirements: Ph.D. in psychology and strong record of teaching. The successful applicant will teach assigned courses and participate in Departmental service as required. There is no research expectation for this position. Our standard teaching load is three courses per semester for lecturers. Applicants should show a commitment to sustain and advance the goals of the institution?s diversity of students, faculty, and staff. Review of applications begins immediately and will continue until the position is filled. Upload cover letter, curriculum vitae, statement describing teaching interests, statement describing experiences and interests in promoting diversity, reprints, teaching evaluations, and have three referees submit letters to https://jobs.usnh.edu/postings/42341. Questions may be sent via email to Search Chair Jill McGaughy (j.mcgaughy at unh.edu). The University of New Hampshire, an R1 Carnegie Classification research university, provides comprehensive, high-quality undergraduate programs and graduate programs of distinction. UNH is located in Durham, NH (population 16,500), on a 188-acre campus, 65 miles north of Boston/Cambridge, 70 miles south of the White Mountain National Forest, and 15 miles from the Atlantic coast. The university has an enrollment of 16,000 students from all 50 states and 71 countries, a full-time faculty of over 900, and offers more than 200 undergraduate and graduate degree programs. The Department offers B.A. and Ph.D. degrees in psychology and hosts an inter-college B.S. major in neuroscience and behavior. Best wishes, Bill Wm Wren Stine Chair, Department of Psychology Program in Neuroscience & Behavior McConnell Hall University of New Hampshire Durham, NH 03824 USA +01 (603) 862-2823 bill.stine at unh.edu TTY: 7-1-1 or +01 (800) 735-2964 (Relay NH) https://unh.zoom.us/j/9372229656 -------------- next part -------------- An HTML attachment was scrubbed... URL: From smart at neuralcorrelate.com Tue Aug 17 00:16:51 2021 From: smart at neuralcorrelate.com (smart at neuralcorrelate.com) Date: Tue, 17 Aug 2021 00:16:51 -0400 Subject: Connectionists: CALL FOR ILLUSION SUBMISSIONS: THE WORLD'S 17TH ANNUAL BEST ILLUSION OF THE YEAR CONTEST In-Reply-To: <0dd501d7931e$47268e10$d573aa30$@neuralcorrelate.com> References: <0ba801d792f8$b73f4280$25bdc780$@neuralcorrelate.com> <0d9301d7931c$4f7ae360$ee70aa20$@neuralcorrelate.com> <0da201d7931c$7c0c0990$74241cb0$@neuralcorrelate.com> <0dd501d7931e$47268e10$d573aa30$@neuralcorrelate.com> Message-ID: <0de401d7931e$b44a0210$1cde0630$@neuralcorrelate.com> **** CALL FOR ILLUSION SUBMISSIONS: THE WORLD'S 17TH ANNUAL BEST ILLUSION OF THE YEAR CONTEST**** http://illusionoftheyear.com We are happy to announce the 17th edition of world's Best Illusion of the YearSM Contest!! Submissions are now welcome! In 2015, the Best Illusion of the YearSM Contest became an annual online event, with the goal of bringing the creativity of the illusion creator community all around the world. Anybody with an internet connection can participate! No matter where you live, you can be a contestant, and/or vote for the Top 3 winners! Contestants are invited to submit 1-minute YouTube or mp4 videos featuring novel illusions (unpublished or published no earlier than 2020) of all sensory modalities (visual, auditory, etc.) and/or cognitive nature. Novel variants of known illusions are welcome. The content of the 1-minute video presenting your illusion is solely up to you, and the only requirement is that it wows all viewers! Some examples include, but are not limited to: * A slide presentation, or succession of images, with a voice over (and/or written text, if you prefer) * A video of yourself describing your illusion * A video animation/theatrical performance of your illusion An international panel of impartial judges will rate all the videos and narrow them down to the Top 10. Then, online voters around the world will choose their favorite illusions from the Top 10 finalists. All Top 10 finalists will receive a commemorative plaque. In addition, the Top 3 winners will receive cash prizes: $3,000 USD for first place; $2,000 USD for second place, and $1,000 USD for third place. The Judge Panel will rate illusions according to: * Significance to our understanding of the human mind and brain * Simplicity of the description * Sheer beauty * Counterintuitive quality * Spectacularity Submissions will be held in strict confidence by the Judge Panel. Only the Top 10 illusions will be posted online, to allow worldwide voting. Participation in the Best Illusion of the YearSM Contest does not preclude you from also submitting your work for publication elsewhere. By participating in the Best Illusion of the YearSM Contest you agree to have your illusion posted on the Contest website, if selected among the Top 10, and included in press releases and other promotional materials/fundraising initiatives for the Contest. You (and your co-authors, if appropriate) will retain the full copyright of your illusion and receive full credit as illusion creator(s). Illusions submitted to previous editions of the contest can be re-submitted to the 2021 Contest, as long as they meet the above requirements and were not among the Top 10 finalists in previous years. You can send your 1-minute video to Susana Martinez-Conde via email ( smart at neuralcorrelate.com) until September 27th, 2021. On behalf of the Executive Board of the Neural Correlate Society: Jose-Manuel Alonso, Stephen Macknik, Susana Martinez-Conde, Luis Martinez, Xoana Troncoso, Peter Tse ---------------------------------------------------------- Susana Martinez-Conde, PhD Author, Champions of Illusion and Sleights of Mind Professor of Ophthalmology, Neurology, and Physiology & Pharmacology Director, Laboratory of Integrative Neuroscience Empire Innovator Scholar State University of New York (SUNY) Downstate Health Sciences University 450 Clarkson Ave, Brooklyn NY 11203, USA Email: smart at neuralcorrelate.com Phone: +1 718-270-4520 http://smc.neuralcorrelate.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From confaiforpeople at gmail.com Mon Aug 16 14:52:29 2021 From: confaiforpeople at gmail.com (Conf. AI for People) Date: Mon, 16 Aug 2021 11:52:29 -0700 Subject: Connectionists: =?utf-8?q?CFP=3A_Call_for_papers_for_the_Internat?= =?utf-8?q?ional_Conference_=E2=80=9CAI_for_People=3A_Towards_Susta?= =?utf-8?b?aW5hYmxlIEFJ4oCdIChDQUlQ4oCZMjEp?= Message-ID: Dear Colleague, we are writing to you as we understand you may be interested in this year?s edition of the International Conference ?AI for People: Towards Sustainable AI? (CAIP?21). Below you will find the official Call for Full papers. Please feel free to distribute it to mailing lists you manage and to everybody who may be interested. Thank you and we hope to see you in CAIP?21! Follow us at: http://aiforpeople.org/conference https://www.linkedin.com/company/19176054/ https://www.facebook.com/aiforpeople https://twitter.com/AIforPeople https://www.instagram.com/ai_for_people/ ------------------------------------------------ International Conference ?AI for People: Towards Sustainable AI? (CAIP?21) November 20-24, 2021 Call for Full Papers https://aiforpeople.org/conference/cfp.php Please distribute (Apologies for cross-posting) If you wish to receive more information about CAIP?21 https://mailchi.mp/281085ba7b4b/caip21 ------------------------------------------------ The International Conference ?AI for People: Towards Sustainable AI? was born out of the idea of shaping Artificial Intelligence technology around human and societal needs. While Artificial Intelligence (AI) can be a beneficial tool, its development and its deployment impact society and the environment in ways that need to be thoroughly addressed and confronted. This year?s edition will focus on Sustainable AI, covering different aspects of social development, environmental protection, and economic growth applied in the design and deployment of AI systems. The conference will provide its participants with opportunities to gain a better understanding of the major challenges of utilizing AI for the societal good. Additionally, it should serve as an incubator for interdisciplinary communities that share a research agenda to exchange and discuss ideas related to the design and application of Sustainable AI. Here, Sustainable AI is a movement to foster change towards greater ecological integrity and social justice in the entire life cycle of AI systems. *** Themes and Topics *** The conference will be interdisciplinary and it welcomes contributions from different disciplines, spanning from computer science, the social sciences, and the humanities. Possible topics include but are not limited to: - AI applications for the social good and towards sustainable development goals - Ethics of Artificial Intelligence - Sustainable AI for Smart Cities - Policy recommendations for Sustainable AI - Green AI for environmental protection - Accuracy and Robustness of AI systems - Bias and Fairness in AI Systems - Privacy and Accountability in AI Systems - Safety and Security in AI Systems - Explainability and Transparency in AI Systems *** Important Dates *** Submission deadline: October 1st, 2021 Notification: November 1st, 2021 Camera-ready: November 6th, 2021 Conference Days: November 20-24, 2021 *** EAI Proceedings *** Conference proceedings will be published in the EAI CORE Proceedings and included in the European Digital Library (EUDL) and will be submitted for inclusion in leading indexing services, including Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP. *** Organising Committee *** The International Conference on ?AI for People: Towards Sustainable AI? is organized by the nonprofit international organization ?AI for People? (aiforpeople.org). - General Chairs: Marta Ziosi (Oxford Internet Institute, University Oxford), Philipp Wicke (University College, Dublin) and Jo?o Miguel Cunha (University of Coimbra), Angelo Trotta (University of Bologna) - Program Chairs: Lea Buchhorn (Leiden University) and Vincenzo Lomonaco (University of Pisa) - Finance Chair: Aina Turillazzi (Tilburg University) - Publication Chair: Angelo Trotta (University of Bologna) - Technical Program Committee: Kevin Trebing (Plan D GmbH) and Gabriele Graffieti (University of Bologna) CAIP'21 is technically sponsored by: EAI. CAIP'21 is supported by: EurAI. From liufengchaos at gmail.com Tue Aug 17 10:15:03 2021 From: liufengchaos at gmail.com (Feng Liu) Date: Tue, 17 Aug 2021 10:15:03 -0400 Subject: Connectionists: CfP: Call for Paper Frontiers in Neuroscience: Special Issue "Graph Learning for Brain Imaging" Message-ID: Dear Colleague, We are writing to you know that we are organizing a special issue "Graph Learning for Brain Imaging" in Frontiers in Neuroscience (impact factor 4.7). We believe this is a timely issue to showcase the new developments using graph representation, deep learning on graph-structured data to address important brain imaging and computational neuroscience problems. *Link*: https://www.frontiersin.org/research-topics/23683/graph-learning-for-brain-imaging *Keywords*: Brain Networks, Graph Neural Networks, Brain Imaging, Graph Embedding, Multi-Modal Imaging. *Topics*: We are looking for original, high-quality submissions on innovative research and developments in the analysis of brain imaging using graph learning techniques. Topics of interest include (but are not limited to): ? Graph neural networks (GNN) for network neuroscience applications ? Graph neural network for brain mapping and data integration ? Graph convolution network (GCN) for brain disorder classification ? (Dynamic) Functional brain networks ? Brain networks development trajectories ? Graphical model for brain imaging data analysis ? Spatial-temporal brain network modeling ? Graph embedding and graph representation learning ? Information fusion for brain networks from multiple modalities or scales (fMRI, M/EEG, DTI, PET, genetics) ? Generative graph models in brain imaging ? Brain network inference: scalable, online, and from non-linear relationships ? Machine learning over graphs: kernel-based techniques, clustering methods, scalable algorithms for brain imaging ? A few-shot learning for learning from limited brain data ? Graph federated learning for brain imaging *Important Dates*: Abstract: 30-Sep-2021 Full paper: 30-Dec-2021 *Background:* Unprecedented collections of large-scale brain imaging data, such as MRI, PET, fMRI, M/EEG, DTI, etc. provide a unique opportunity to deepen our understanding of the brain working mechanisms, improve prognostic predictions for mental disorders, and tailor personalized treatment plans for brain diseases. Recent advances in machine learning and large-scale brain imaging data collection, storage, and sharing lead to a series of novel interdisciplinary approaches among the fields of computational neuroscience, signal processing, deep learning, brain imaging, cognitive science, and computational psychiatry, among which graph learning provides a valuable means to address important questions in brain imaging. Graph learning refers to designing effective machine learning and deep learning methods extracting important information from graphs or exploiting the graph structure in the data to guide the knowledge discovery. Given the complex data structure in different imaging modalities as well as the networked organizational structure of the human brain, novel learning methods based on graphs inferred from imaging data, graph regularizations for the data, and graph embedding of the recorded data, have shown great promise in modeling the interactions of multiple brain regions, information fusion among networks derived from different brain imaging modalities, latent space modeling of the high dimensional brain networks, and quantifying topological neurobiomarkers. The goal of this Research Topic is to synergize the start-of-the-art discoveries in terms of new computational brain imaging models and insights of brain mechanisms through the lens of brain networks and graph learning. --On Behalf of all the Guest Editors Feng Liu, Stevens Institute of Technology, Hoboken, NJ, USA Yu Zhang, Lehigh University, Bethlehem, PA, USA Jordi Sol?-Casals, Universitat de Vic - Universitat Central de Catalunya, Barcelona, SpainIslem Rekik, Istanbul Technical University, Istanbul, TurkeyYehia Massoud, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia -------------- next part -------------- An HTML attachment was scrubbed... URL: From mario.a at samsung.com Tue Aug 17 10:49:46 2021 From: mario.a at samsung.com (Mario Pinto de Almeida) Date: Tue, 17 Aug 2021 15:49:46 +0100 Subject: Connectionists: 2nd Workshop on Distributed Machine Learning, co-located with CoNEXT 2021 References: Message-ID: <20210817144946eucms1p107039eb0dd1e1cdac97b884b5d0dd53f@eucms1p1> An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: image/gif Size: 13168 bytes Desc: not available URL: From schockaerts1 at cardiff.ac.uk Tue Aug 17 15:09:54 2021 From: schockaerts1 at cardiff.ac.uk (Steven Schockaert) Date: Tue, 17 Aug 2021 19:09:54 +0000 Subject: Connectionists: Postdoctoral position at Cardiff University Message-ID: <7BF9CEE6-3B30-4DBF-86D4-C3267C03C19F@cardiff.ac.uk> Keywords: graph neural networks, commonsense reasoning, learning & reasoning, ontologies, rule based methods Deadline: 26th August 2021 Location: Cardiff University, UK More details: https://www.jobs.ac.uk/job/CIF388/research-associate We offer a three-year postdoctoral position at Cardiff University to work on a project on ?Plausible Reasoning with Ontologies using Graph Neural Networks? funded by the Leverhulme Trust. The aim of this project is to study how the complementary strengths of graph neural networks and rule based methods can be combined. To this end, we will use the latent representations of GNNs to allow for a kind of commonsense reasoning with symbolic rules, allowing us to draw plausible conclusions which go beyond what can be logically deduced. -------------- next part -------------- An HTML attachment was scrubbed... URL: From hocine.cherifi at gmail.com Wed Aug 18 06:00:01 2021 From: hocine.cherifi at gmail.com (Hocine Cherifi) Date: Wed, 18 Aug 2021 12:00:01 +0200 Subject: Connectionists: CFP COMPLEX NETWORKS 2021| Hybrid | Submission deadline: 01 Sep 2021 Message-ID: *10th** International Conference on Complex Networks & Their Applications* *Hybrid- Madrid, Spain *November 30 - December 02, 2021 COMPLEX NETWORKS 2021 You are cordially invited to submit your contribution until September 01, 2021. *SPEAKERS * ? Marc Barth?l?my CEA France ? Ginestra Bianconi Queen Mary University of London UK ? Jo?o Gama University of Porto Portugal ? Dirk Helbing ETH Z?rich Switzerland ? Yizhou Sun UCLA USA ? Alessandro Vespignani Northeastern University USA *TUTORIALS (November 29, 2021)* ? Elisabeth Lex Graz University of Technology Austria ? Giovanni Petri ISI Foundation Italy *PUBLICATION* Full papers (not previously published up to 12 pages) and Extended Abstracts (about published or unpublished research up to 3 pages) are welcome. ? *Papers *will be included in the conference *proceedings edited by Springer* ? *Extended abstracts* will be published in the *Book of Abstracts (with ISBN)* Templates are available on the submission webpage. If in doubt, please contact the Publication Chair (matteo.zignani at unimi.it) All contributions should be submitted via EasyChair . Extended versions will be invited for publication in *special issues of international journals:* o Applied Network Science edited by Springer o Complex Systems o Computational Social Networks edited by Springer o Network Science edited by Cambridge University Press o PLOS one o Social Network Analysis and Mining edited by Springer *TOPICS* *Topics include, but are not limited to: * o Models of Complex Networks o Structural Network Properties and Analysis o Complex Networks and Epidemics o Community Structure in Networks o Community Discovery in Complex Networks o Motif Discovery in Complex Networks o Network Mining o Network embedding methods o Machine learning with graphs o Dynamics and Evolution Patterns of Complex Networks o Link Prediction o Multilayer Networks o Network Controllability o Synchronization in Networks o Visual Representation of Complex Networks o Large-scale Graph Analytics o Social Reputation, Influence, and Trust o Information Spreading in Social Media o Rumour and Viral Marketing in Social Networks o Recommendation Systems and Complex Networks o Financial and Economic Networks o Complex Networks and Mobility o Biological and Technological Networks o Mobile call Networks o Bioinformatics and Earth Sciences Applications o Resilience and Robustness of Complex Networks o Complex Networks for Physical Infrastructures o Complex Networks, Smart Cities and Smart Grids o Political networks o Supply chain networks o Complex networks and information systems o Complex networks and CPS/IoT o Graph signal processing o Cognitive Network Science o Network Medicine o Network Neuroscience o Quantifying success through network analysis o Temporal and spatial networks o Historical Networks *GENERAL CHAIRS* Rosa Maria Benito *Universidad Politecnica de Madrid, Spain* Hocine Cherifi *University of Burgundy, France* Esteban Moro *Universidad Carlos III de Madrid, Spain* *ADVISORY BOARD* Jon Crowcroft *University of Cambridge, UK* Raissa D'Souza *UC Davis, USA* Eugene Stanley *Boston University, USA* Ben Y. Zhao *University of Chicago, USA* *PROGRAM CHAIRS* Chantal Cherifi *University of Lyon, France* Luis M. Rocha *Indiana University, USA* Marta Sales-Pardo *Universitat Rovira i Virgili, Spain* *LIGHTNING CHAIRS* Jes?s Gomez Garde?es *University of Zaragoza, Spain* Regino Criado* Universidad Rey Juan Carlos de Madrid, Spain* Huijuan Wang *TU Delft, Netherlands* *POSTER CHAIRS* Manuel Marques Pita *Universidade Lus?fona, Portugal* Taha Yasseri *University of Oxford, UK* Jos? Javier Ramasco *IFISC, Spain* *TUTORIAL CHAIRS* Luca Maria Aiello *Nokia-Bell Labs, UK* Leto Peel *Universit? Catholique de Louvain, Belgium* *SATELLITE CHAIR* Javier Galeano *Universidad Politecnica de Madrid, Spain* *PUBLICITY CHAIRS* Benjamin Renoust *Osaka University, Japan* Xiangjie Kong* Dalian* *University of Technology, China* *SPONSOR CHAIR* Roberto Interdonato *CIRAD, France* *STUDENT GRANT CHAIR* Sabrina Gaito *Universit? degli Studi di Milano, Italy* *PUBLICATION CHAIR* Matteo Zignani *Universit? degli Studi di Milano, Italy* *WEB CHAIR* Stephany Rajeh *University of Burgundy, France* *LOCAL COMMITTEE CHAIR* Juan Carlos Losada *Universidad Politecnica de Madrid, Spain* Join us at COMPLEX NETWORKS 2021 Madrid Spain *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comt? Deputy Director LIB EA N? 7534 Editor in Chief Applied Network Science Editorial Board member PLOS One , IEEE ACCESS , Scientific Reports , Journal of Imaging , Quality and Quantity , Computational Social Networks , Complex Systems Complexity -------------- next part -------------- An HTML attachment was scrubbed... URL: From mail at mkaiser.de Thu Aug 19 10:08:24 2021 From: mail at mkaiser.de (Marcus Kaiser) Date: Thu, 19 Aug 2021 15:08:24 +0100 Subject: Connectionists: Faculty research fellowships ('tenure-track') available at the University of Nottingham Message-ID: Dear all, New recruitment round launched for Nottingham Research and Anne McLaren Fellowship schemes! Join a cohort of ambitious and exceptional early-career researchers. Generous funding, research expenses, childcare costs, leadership mentoring + more. We have two schemes, each offering the same package of support: - *Anne McLaren Fellowships* are aimed at outstanding female postdoctoral researchers in science, technology, engineering and medicine, who are at the early stage of their academic careers and wish to establish a research career in the UK - *Nottingham Research Fellowships* are aimed at outstanding postdoctoral researchers who are at the early stage of their academic careers from all academic disciplines represented at the university We offer: - three years? independent research funding, covering salary costs at c. ?40,000-49,000 - *the link to a permanent academic post, subject to performance* - additional funding for research expenses totalling ?75,000 - childcare costs of up to ?15,000 - access to mentoring, career development and networking with the wider fellowship community Find out more at: https://www.nottingham.ac.uk/research/researchwithus/fellowships/nottingham/index.aspx Nottingham ?the home of MRI? offers an excellent environment for imaging ( https://www.nottingham.ac.uk/research/beacons-of-excellence/precision-imaging/ and https://www.nottingham.ac.uk/research/groups/spmic/index.aspx ), is pioneering the use of neurotechnology for brain disorders ( http://mindtech.org.uk/ ), hosts the Institute of Mental Health ( https://www.institutemh.org.uk ), and has a large group of faculty members including four full professors (Stephen Coombes, Mark van Rossum, Mark Humphries, Marcus Kaiser) in the area of computational/mathematical neuroscience. Please contact me if you want to find out more about how your research might fit in with our priorities of connectomics, brain stimulation, neurotechnology, neuroimaging, and computational/mathematical neuroscience. Best, Marcus -- *Marcus Kaiser, Ph.D. FRSB* @ConnectomeLab *Professor of Neuroinformatics* *Precision Imaging Beacon, School of Medicine, University of Nottingham* Guanci Visiting Professor Rui Jin Hospital, Shanghai Jiao Tong University, China Book: Changing Connectomes https://mitpress.mit.edu/books/changing-connectomes Lab website: http://www.dynamic-connectome.org/ Neuroinformatics UK: http://www.neuroinformatics.org.uk/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From d.bach at ucl.ac.uk Fri Aug 20 02:44:34 2021 From: d.bach at ucl.ac.uk (Dominik R. Bach) Date: Fri, 20 Aug 2021 08:44:34 +0200 Subject: Connectionists: 4 days left to apply: Post doc in cognitive neuroscience/virtual reality research at University College London (movement trajectories, wearable MEG) In-Reply-To: <1125ca50-9269-9fb5-7c76-f8296faa41ca@ucl.ac.uk> References: <1125ca50-9269-9fb5-7c76-f8296faa41ca@ucl.ac.uk> Message-ID: We are looking for a research fellow in an ERC-funded research project "Action selection under threat - the complex control of human defence" led by Dominik Bach (http://bachlab.org ) at University College London. The position will be based at the Max-Planck UCL Centre for Computational Psychiatry (https://www.mps-ucl-centre.mpg.de/en ). OPM-MEG research takes place at the Wellcome Centre for Human Neuroimaging (http://www.fil.ion.ucl.ac.uk/ ). Our immersive virtual reality lab is based at the UCL Department for Clinical and Movement Neuroscience. These places offer world-class training and networking opportunities and an intellectually vibrant and inspiring research culture. The overarching goal of the project is to understand the computational algorithms of decision-making under acute, immediate threat. We investigate this in an immersive virtual reality (VR) environment, in which people can move to avoid a large number of different threats. The candidate will design and perform human behavioural experiments and analyse movement trajectories. They will also develop and perform MEG experiments using wearable sensors (OPM). The role requires a good understanding of human VR experimentation as well as an interest in using wearable MEG. The interdisciplinary project team is composed of VR experts, psychologists, movement scientists, and decision theorists, and we are looking for an individual who enjoys working in a team environment. Within the topical focus, the project offers freedom to explore and develop novel experimental manipulations that allow inference on the mechanisms of decision-making and action selection. Successful applicants will have an established track record of experimental human research using virtual reality or OPMs, and a strong interest in combining both. They will have a PhD in cognitive-computational (neuro)science, applied machine-learning, motor science, a quantitative field of psychology (e.g. decision-making, perception), or a related area by the agreed start date of the position. They will be keen to solve technical challenges. We are looking for an individual who is strongly motivated to pursue an academic career and is excited by the opportunities for personal and career development this position can provide. The post is available from October 2021 and funded for up to 3 years. Starting salary is on UCL grade 7, ranging from ?36,028 to ?43,533 per annum, inclusive of London Allowance, superannuable. More information and access to the UCL online application portal: https://is.gd/sOiFPc Please contact d.bach at ucl.ac.uk for any queries about the project or role. *Closing date: 24 August* Interviews will be held remotely 1-3 September. Apologies for cross-posting. -- ----------------------- Dominik R Bach MBBS PhD Principal Research Fellow Max Planck UCL Centre for Computational Psychiatry and Ageing Research Wellcome Centre for Human Neuroimaging, University College London bachlab.org | @bachlab_cog -------------- next part -------------- An HTML attachment was scrubbed... URL: From dwang at cse.ohio-state.edu Thu Aug 19 21:25:39 2021 From: dwang at cse.ohio-state.edu (Wang, Deliang) Date: Fri, 20 Aug 2021 01:25:39 +0000 Subject: Connectionists: Call for Nominations: Neural Networks Best Paper Award Message-ID: Please see this year's Call for Nominations with the deadline of Sept. 30: https://www.journals.elsevier.com/neural-networks/announcements/call-for-nominations-neural-networks-best-paper-award-2021 Information about the award is given below: https://www.journals.elsevier.com/neural-networks/news/neural-networks-best-paper-award Thanks, Kenji Doya and DeLiang Wang Co-Editors-in-Chief, Neural Networks -------------- next part -------------- An HTML attachment was scrubbed... URL: From michel.verleysen at uclouvain.be Wed Aug 18 07:14:55 2021 From: michel.verleysen at uclouvain.be (Michel Verleysen) Date: Wed, 18 Aug 2021 11:14:55 +0000 Subject: Connectionists: ESANN 2021 call for participation Message-ID: ESANN 2021 - 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning Online event, 6-8 October 2021 https://www.esann.org Call for participation Registration is open until 30.09.2021 at https://www.esann.org. Reduced registration fees apply until 24.08.2021. Program The full conference program is available as https://www.esann.org/node/8. Online format The conference will keep its traditional single-track format. An online conference platform will be used, providing live streams and pre-recorded videos accessible through both desktop and mobile interfaces. The program includes full talks with Q/A slots, and short spotlights introducing poster presentations. Posters sessions will be organized in an interactive and live environment. Scope and topics The ESANN conferences cover machine learning, artificial neural networks, statistical information processing and computational intelligence. Mathematical foundations, algorithms and tools, and applications are covered. In addition to regular sessions, 6 special sessions will be organized on the following topics: - Complex Data: Learning Trustworthily, Automatically, and with Guarantees - Federated Learning - Methods, Applications and Beyond - Deep learning for graphs - Interpretable Models in Machine Learning and Explainable Artificial Intelligence - Machine Learning for Measuring and Analyzing Online Social Communications - Machine learning and data mining for urban mobility intelligence ESANN 2021 builds upon a successful series of conferences organized each year since 1993. ESANN has become a major scientific event in the machine learning, computational intelligence and artificial neural networks fields over the years. ======================================================== ESANN - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning http://www.esann.org/ * For submissions of papers, reviews, registrations: Michel Verleysen UCLouvain - Machine Learning Group 3, pl. du Levant - B-1348 Louvain-la-Neuve - Belgium tel: +32 10 47 25 51 - fax: + 32 10 47 25 98 mailto:esann at uclouvain.be * Conference secretariat d-side conference services 24 av. L. Mommaerts - B-1140 Evere - Belgium tel: + 32 2 730 06 11 - fax: + 32 2 730 06 00 mailto:esann at uclouvain.be ======================================================== -------------- next part -------------- An HTML attachment was scrubbed... URL: From ASJagath at ntu.edu.sg Wed Aug 18 20:11:32 2021 From: ASJagath at ntu.edu.sg (Jagath C Rajapakse (Prof)) Date: Thu, 19 Aug 2021 00:11:32 +0000 Subject: Connectionists: Postdoctoral Research Fellow in Connectome Analysis using functional MRI and DTI scans In-Reply-To: References: Message-ID: Postdoctoral Research Fellow in Connectome Analysis using functional MRI and DTI scans School of Computer Science and Engineering Nanyang Technological University, Singapore A postdoctoral research fellow position is available in brain image analysis in the Biomedical Computing Group headed by Professor Jagath Rajapakse, Nanyang Technological University, Singapore, for a period of three years. The candidate will build upon recent research on encoding and decoding the functional and structural connectome by using deep neural networks. Encoding learns compact representations of the connectome, leading to disease classification, subtype identification, etc., and decoding is aimed at identifying key brain regions and connections implicated in brain diseases. The candidate will investigate recent Graph Neural Networks such as GCN, GraphSAGE, and GAT for connectome analysis from fMRI and DTI scans. A key challenge to deep learning approaches of modelling the connectome is the lack of large imaging datasets. Reference: S. Gupta, Y. H. Chen, and J. C. Rajapakse, ?Obtaining leaner deep neural networks for decoding brain functional connectome in a single shot,? Neurocomputing, January, 2021. DOI: 10.1016/j.neucom.2020.04.152 The candidate would have expertise and skills in image analysis, machine learning, and Python/R programming, and a PhD in a related field. Salary is S$6000-7000, depending on experience. Interested candidates are to email their CV to asjagath at ntu.edu.sg: Professor Jagath Rajapakse https://personal.ntu.edu.sg/asjagath/ ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: postdoc_BrainImageAnalysis.pdf Type: application/pdf Size: 58038 bytes Desc: postdoc_BrainImageAnalysis.pdf URL: From Nantia.Makrynioti at cwi.nl Thu Aug 19 05:06:12 2021 From: Nantia.Makrynioti at cwi.nl (Nantia Makrynioti) Date: Thu, 19 Aug 2021 11:06:12 +0200 (CEST) Subject: Connectionists: CfP: Workshop on Databases and AI @NeurIPS 2021 Message-ID: <917486315.23200335.1629363972828.JavaMail.zimbra@cwi.nl> Call for Papers --------------------------------------------------------------------------------------- DBAI Workshop on Databases and AI @NeurIPS 2021 https://dbai-workshop.github.io/ Co-located with NeurIPS 2021 (Virtual conference) About the workshop --------------------------------------------------------------------------------------- Relational data represents the vast majority of data present in the enterprise world. Yet none of the ML computations happens inside a relational database where data reside. Instead a lot of time is wasted in denormalizing the data and moving them outside of the databases in order to train models. Relational learning, which takes advantage of relational data structure, has been a 20 year old research area, but it hasn?t been connected with relational database systems, despite the fact that relational databases are the natural space for storing relational data. Recent advances in database research have shown that it is possible to take advantage of the relational structure in data in order to accelerate ML algorithms. Research in relational algebra originating from the database community has shown that it is possible to further accelerate linear algebra operations. Probabilistic Programming has also been proposed as a framework for AI that fits can be realized in relational databases. Data programming, a mechanism for weak/self supervision is slowly migrating to the natural space of storing data, the database. At last as models in deep learning grow several systems are being developed for model management inside relational databases. This workshop aspires to start a conversation on the following topics: - What is the impact of relations/relational structure in machine learning? - Why has relational learning not been more successful? Why we don?t have yet the equivalent of tensorflow/pytorch in relational learning? - Why is there no deep network structure for structured relational data? Are we just not there yet, or is there something intrinsic in random forest/boosted trees that work better for relational data? - Can relational databases take advantage of the relational nature of graph neural network - The algorithms and db communities have completely different approaches to relational learning, what is the connection? - How does data programming connect to relational learning and can it be accelerated with the algorithmic primitives of relational databases? - The attention network has been interpreted and used as a mechanism for discovering and expressing relations. It has also been considered as a storage mechanism of knowledge in Large Language Models (Transformers). Are transformers equivalent to databases? Call for papers --------------------------------------------------------------------------------------- Areas of particular interest for the workshop include (but are not limited to): * Data Management in Machine Learning Applications * Definition, Execution and Optimization of Complex Machine Learning Pipelines * Systems for Managing the Lifecycle of Machine Learning Models * Systems for Efficient Hyperparameter Search and Feature Selection * Machine Learning Services in the Cloud * Modeling, Storage and Provenance of Machine Learning Artifacts * Integration of Machine Learning and Dataflow Systems * Integration of Machine Learning and ETL Processing * Definition and Execution of Complex Ensemble Predictors * Sourcing, Labeling, Integrating, and Cleaning Data for Machine Learning * Data Validation and Model Debugging Techniques * Privacy-preserving Machine Learning * Benchmarking of Machine Learning Applications * Responsible Data Management * Transparency and Accountability of Machine-Assisted Decision Making * Impact of Data Quality and Data Preprocessing on the Fairness of ML Predictions Submission: Submissions can be short papers (4 pages) or long papers (up to 8 pages, plus unlimited references). Authors are requested to prepare submissions following the NeurIPS proceedings format. DBAI is a single-blind workshop, authors must include their names and affiliations on the manuscript cover page. Submission Website: TBD Inclusion and Diversity in Writing: http://2021.sigmod.org/calls_papers_inclusion_and_diversity.shtml Conflicts: Workshops are not a venue for work that has been previously published in other conferences on machine learning or related fields. Work that is presented at the main NeurIPS conference wiil not be accepted in the workshop, including as part of an invited talk. Important Dates --------------------------------------------------------------------------------------- Paper submission deadline: Sep 17, 2021, 11:59 PM (AoE, UTC-12) Acceptance notification: Oct 22, 2021 EOD Mandatory SlidesLive upload for speaker videos: Nov 08, 2021 Workshop day: Dec 13, 2021 Organizers --------------------------------------------------------------------------------------- Nikolaos Vasiloglou (relationalAI) Maximilian Schleich (University of Washington) Nantia Makrynioti (CWI) Parisa Kordjamshidi (Michigan State University) Kirk Pruhs (University of Pitsburg) Zenna Tavares (MIT) From ioannakoroni at csd.auth.gr Thu Aug 19 00:54:05 2021 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Thu, 19 Aug 2021 07:54:05 +0300 Subject: Connectionists: Invitation to join 2021 Summer 'Programming short course and workshop on Deep Learning and Computer Vision', 25-27th August 2021 Message-ID: <0afd01d794b6$3d948020$b8bd8060$@csd.auth.gr> Dear Machine Learning and Deep Neural Networks engineers, scientists and enthusiasts, you are welcomed to register in the CVML e-course on 'Programming short course and workshop on Deep Learning and Computer Vision', 25-27th August 2021: http://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-deep -learning-and-computer-vision-for-autonomous-systems-2021/ It will take place as a three-day e-course (due to COVID-19 circumstances), hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece, providing a series of live lectures and workshops delivered through a tele-education platform (Zoom). They will be complemented with on-line video recorded lectures and lecture pdfs, to facilitate international participants having time difference issues and to enable you to study at own pace. You can also self-assess your knowledge, by filling appropriate questionnaires (one per lecture). You will be provided programming to improve your programming skills. You will also have accesses to tutorial exercises to better your theoretical understanding of selected CVML topics. This course is part of the very successful CVML programming short course and workshop series that took place in the last four years. Course description 'Programming short course and workshop on Deep Learning and Computer Vision' The programming short course and workshop e-course consists of 16 1-hour live lectures & workshops organized in two Parts (1 Part per day): Part A will focus on Deep Learning and GPU programming. Part B lectures will focus on deep learning algorithms for computer vision, namely on 2D object/face detection and 2D object tracking. Part C lectures will focus on autonomous UAV cinematography. Before mission execution, it is best simulated, using drone mission simulation tools. Course lectures Part A (8 hours), Deep Learning and GPU programming Deep neural networks. Convolutional NNs. Deep learning for target detection. Image classification with CNNs. Target detection with PyTorch. Part B (8 hours), Deep Learning for Computer Vision Deep learning for object/face detection. 2D object tracking. PyTorch: Understand the core functionalities of an object detector. Training and deployment. OpenCV programming for object tracking. Part C (8 hours), Autonomous UAV cinematography Video summarization. UAV cinematography. Video summarization with Pytorch. Drone cinematography with Airsim. You can use the following link for course registration: http://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-deep -learning-and-computer-vision-for-autonomous-systems-2021/ Lecture topics, sample lecture ppts and videos, self-assessment questionnaires, programming exercises and tutorial exercises can be found therein. For questions, please contact: Ioanna Koroni > The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow and IEEE distinguished speaker. He is the coordinator of the EC funded International AI Doctoral Academy (AIDA ), that is co-sponsored by all 5 European AI R&D flagship projects (H2020 ICT48). He was initiator and first Chair of the IEEE SPS Autonomous Systems Initiative. He is Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece. He was Coordinator of the European Horizon2020 R&D project Multidrone. He is ranked 249-top Computer Science and Electronics scientist internationally by Guide2research (2018). He has 33800+ citations to his work and h-index 86+. AUTH is ranked 153/182 internationally in Computer Science/Engineering, respectively, in USNews ranking. Relevant links: 1) Prof. I. Pitas: https://scholar.google.gr/citations?user=lWmGADwAAAAJ &hl=el 2) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/ 3) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/ 4) International AI Doctoral Academy (AIDA): http://www.i-aida.org/ 5) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/ 6) AIIA Lab: https://aiia.csd.auth.gr/ Sincerely yours Prof. I. Pitas Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab) Aristotle University of Thessaloniki, Greece Post scriptum: To stay current on CVML matters, you may want to register in the CVML email list, following instructions in: https://lists.auth.gr/sympa/info/cvml Virus-free. www.avast.com -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: ~WRD0000.jpg Type: image/jpeg Size: 823 bytes Desc: not available URL: From jncor at dei.uc.pt Fri Aug 20 06:49:09 2021 From: jncor at dei.uc.pt (=?UTF-8?Q?Jo=C3=A3o_Nuno_Correia?=) Date: Fri, 20 Aug 2021 11:49:09 +0100 Subject: Connectionists: CfP EvoStar 2022 - The Leading European Event on Bio-Inspired Computation - 20-22 April 2022 Message-ID: Dear Colleague(s), Below you will find the second call for papers for EvoStar 2022. Feel free to distribute and thank you for your time! Best regards, Jo?o Correia EvoStar Publicity Chair ---------------------------------------------------------------------- Call for papers for the EvoStar 2022 conference http://www.evostar.org/2022/ Submission Deadline: November 1, 2021 Conference: 20 to 22 April 2022. Venue: *Somewhere On Earth!* All accepted papers will be printed in the proceedings published by Springer Nature in the Lecture Notes in Computer Science (LNCS) series. Please distribute (Apologies for cross-posting) ------------------------------------------------ ***************************************** News: - EvoApps and EuroGP special joint track on Evolutionary Machine Learning - EvoCop and EvoApps got Core Rank B. - EvoApps is open for Special Sessions with 9 already confirmed: . Applications of Bio-inspired techniques on Social Networks . Applications of Nature-inspired Computing for Sustainability and Development . Evolutionary Computation in Image Analysis, Signal Processing and Pattern Recognition . Machine Learning and AI in Digital Healthcare and Personalized Medicine . Evolutionary Robotics . Parallel and Distributed Systems . Resilient Bio-Inspired Algorithms . Soft Computing applied to Games . Analysis of Evolutionary Computation Methods: Theory, Empirics, and Real-World Applications Deadline for special sessions proposals:10th of September 2021 ****************************************** EvoStar comprises four co-located conferences run each spring at different locations throughout Europe. These events arose out of workshops originally developed by EvoNet, the Network of Excellence in Evolutionary Computing, established by the Information Societies Technology Programme of the European Commission, and they represent a continuity of research collaboration stretching back over 20 years. EvoStar is organised by SPECIES, the Society for the Promotion of Evolutionary Computation in Europe and its Surroundings. This non-profit academic society is committed to promoting evolutionary algorithmic thinking, with the inspiration of parallel algorithms derived from natural processes. It provides a forum for information and exchange. The four conferences include: - EuroGP 25th European Conference on Genetic Programming http://www.evostar.org/2022/eurogp/ - EvoApplications 25th European Conference on the Applications of Evolutionary and bio-inspired Computation http://www.evostar.org/2022/evoapps/ - EvoCOP 22st European Conference on Evolutionary Computation in Combinatorial Optimisation http://www.evostar.org/2022/evocop/ - EvoMUSART 11th International Conference (and 16th European event) on Artificial Intelligence in Music, Sound, Art and Design. http://www.evostar.org/2022/evomusart/ *** Important Dates, Venue and Publication *** Submission Deadline: November 1, 2021 Conference: 20 to 22 April 2022. Venue: *Somewhere on Earth!* All accepted papers will be printed in the proceedings published by Springer Nature in the Lecture Notes in Computer Science (LNCS) series. Please check the website for more information: http://www.evostar.org/2022/ And follow us at: Facebook - https://www.facebook.com/evostarconf/ Twitter - https://twitter.com/EvostarConf/ Instagram - https://www.instagram.com/evostarconference/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From stefano.panzeri at gmail.com Fri Aug 20 07:41:11 2021 From: stefano.panzeri at gmail.com (Stefano Panzeri) Date: Fri, 20 Aug 2021 13:41:11 +0200 Subject: Connectionists: Postdoc and PhD Positions in Computational Cognitive Neuroscience at UKE - Hamburg Message-ID: The Panzeri and Donner laboratories at the University Medical Center Hamburg-Eppendorf (UKE) aim to fill joint postdoc and PhD positions starting at any time. The vacant positions are for collaborative projects in computational cognitive neuroscience, and funding is available for several years. Applications will be reviewed when they are received until positions are filled. Both labs aim to understand how higher brain functions such as sensation, perception, decision-making, and memory, emerge from the interactions between brain areas and/or populations of neurons within these areas. These topics are studied in the healthy brain and in neuropsychiatric disorders, and they are addressed through a tight interplay between theoretical and experimental approaches. Joint ongoing work focuses on how feedforward and feedback communication across the cortical hierarchy, excitation-inhibition balance, and neuromodulatory processes, shape decision-making. The Panzeri Lab, newly established at UKE Hamburg, is a theoretical lab which develops advanced mathematical tools for brain data analysis, applies these methods to real data to produce new results on neural information processing, and develops biophysically plausible neural network models of how information is processed in the brain. The Donner lab is an experimental lab that combines pharmacological intervention, psychophysics, eye-tracking, and neuroimaging (MEG and fMRI) in human subjects with advanced data analysis and computational modeling tools to uncover signatures and mechanisms of cognitive computation. The new lab members will join existing teams with extensive expertise in both computational and experimental neuroscience. The new lab members will also benefit from both labs? extensive international collaborations including Harvard Medical School, Italian Institute of Technology, Baylor College of Medicine, Cornell University, ?cole Normale Sup?rieure, New York University, Pompeu Fabra University, University of Pennsylvania, SISSA and others. We seek applications from qualified individuals from all demographics, genders, and backgrounds. Both labs are committed to diversity, highly international, and operate in English. Hamburg is a vibrant, international, family-friendly, and green city. It hosts one of the world?s largest harbors, an internationally acclaimed concert hall, a large lake, and dozens of canals, lots of beautiful parks, and many other nice places for leisure time. The UKE also has excellent family-friendly facilities. Candidates should have a solid background in numerate sciences and a keen interest in applying advanced mathematical concepts to reveal the function of the brain. Experience in quantitative or computational neuroscience is a major plus. The main criterion, however, is a commitment to scientific excellence. Applications (full CV, statement of research interest and name and contact of 2 referees) should be sent to t.donner at uke.de , stefano.panzeri at gmail.com Further information on both labs can be found here: http://www.tobiasdonner.net https://www.uke.de/english/departments-institutes/institutes/department-of-excellence-for-neural-information-processing/team/index.html Recent relevant publications of the labs include: Pfeffer, T. et al (2021), Circuit mechanisms for the chemical modulation of cortex-wide network interactions and behavioral variability*. *Science Advances 7: eabf5620 Valente, M., et al (2021), Correlations enhance the behavioral readout of neural population activity in association cortex. Nature Neuroscience, 24, 975?986 Murphy P., et al (2021), Adaptive circuit dynamics across human cortex during evidence accumulation in changing environments. Nature Neuroscience 7: 987-997. Wilming N., et al (2020), Large-scale dynamics of decision information across human cortex. Nature Communications 11: 5109. Chong, E. et al (2020) Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception. Science 368, 1329. Runyan C. A., et al (2017) Distinct timescales of population coding across cortex, Nature: 548: 92-96. Stefano Panzeri, Professor of Neural Information Processing Tobias H. Donner, Professor of Integrative Neuroscience University Medical Center Hamburg-Eppendorf -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiaochun.cheng at gmail.com Fri Aug 20 08:32:21 2021 From: xiaochun.cheng at gmail.com (Xiaochun Cheng) Date: Fri, 20 Aug 2021 13:32:21 +0100 Subject: Connectionists: Cloud Computing Awards Message-ID: <00a801d795bf$6cb4a830$461df890$@gmail.com> Please nominate for the Cloud Computing Awards. 2021 TCCLD Awards announcement : https://tc.computer.org/tccld/awards/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From thanh.dinhvan at gmail.com Fri Aug 20 10:06:51 2021 From: thanh.dinhvan at gmail.com (=?UTF-8?B?xJBpbmggVsSDbiBUaMOgbmg=?=) Date: Fri, 20 Aug 2021 21:06:51 +0700 Subject: Connectionists: Call for KR 2021 Student Scholarship Applications Message-ID: <51ceb418-27c5-cbe7-46cc-a36d1f35ed21@gmail.com> ****************************************** Call for KR 2021 Student Scholarship Applications ****************************************** We are delighted to announce funding for KR 2021 student support. The purpose is to enable students to participate in the conference. To be eligible, you must be registered as a full-time student at a higher education institution (e.g. university). *You can submit your application at the following link:* ************** https://www.isurvey.soton.ac.uk/41031 ************** ** *Please submit your application by 6^th September 2021 via this form. We will notify you of our decision by 8^th September 2021.* In allocating awards, we will prioritise students who are listed as authors of a long or short paper accepted for KR 2021. Please note that attending the conference is a requirement for being supported. In addition, by participating in the student scholarship program, students are expected to support the conference as student volunteers: You may be asked to support the conference in various ways, e.g., to help with running a particular session. Due to NSF requirements, successful US applicants are also asked to participate in the Doctoral Consortium (DC) either as a presenter or as an attendee, with no obligation to have a paper accepted at the DC. US applicants are also asked to write a short report on their attendance at KR. If your application is successful, you will receive a code that you can then use upon registration as a conference fee waiver. Please wait to register for the conference until our notification. We will not reimburse already made payments. For any question, feel free to contact us at KR21virtual+registration at gmail.com or contact Long Tran-Thanh directly at long.tran-thanh at warwick.ac.uk . Thank you, Tran Cao Son, New Mexico State University, US Long Tran-Thanh,University of Warwick, UK On the behalf of the KR 2021 organising committee. -------------- next part -------------- An HTML attachment was scrubbed... URL: From bhammer at techfak.uni-bielefeld.de Fri Aug 20 10:51:21 2021 From: bhammer at techfak.uni-bielefeld.de (Barbara Hammer) Date: Fri, 20 Aug 2021 16:51:21 +0200 Subject: Connectionists: AI starter program Message-ID: <66fb9349-ba7e-0be8-9420-7d26aa985e4d@techfak.uni-bielefeld.de> We would like to draw your attention to the project AI-starter of the federal state NRW, Germany. The program offers project funding up to 175.000 EUR and up to 2 years for junior researchers shortly after their PhD to kickstart a project in the field of fundamental AI. The project can be located at any University in NRW. Applications are due until November 15th 2021 More infos can be found here: https://www.ptj.de/ki-starter -- Prof. Dr. Barbara Hammer Machine Learning Group, CITEC Bielefeld University D-33594 Bielefeld Phone: +49 521 / 106 12115 From Aldo.Romero at mail.wvu.edu Sat Aug 21 17:04:17 2021 From: Aldo.Romero at mail.wvu.edu (Aldo Romero) Date: Sat, 21 Aug 2021 21:04:17 +0000 Subject: Connectionists: Postdoc Announcement WVU Message-ID: Postdoctoral Research Associate - Department of Forensic and Investigative Sciences (ECAS). Position Number 16807 Description The Department of Forensic and Investigative Sciences (FIS) in the Eberly College of Arts and Sciences is seeking applications for a Postdoctoral Research Associate to join Dr. Tatiana Trejos research group to support the project ?Assessing the Strength of Trace Evidence Fracture Fits through a Comprehensive, Systematic, and Quantifiable Approach? The position is funded for one year and requires a proactive and independent researcher to work in collaboration with Dr. Tatiana Trejos at the FIS Department and Dr. Aldo Romero at the Physics and Astronomy Department. The position will be involved in the development of deep learning machine learning algorithms and databases to quantify the quality of a physical edge fit of materials of forensic interest. Successful candidates will perform independent research in the areas of machine learning and imaging, computer science, and statistics, will mentor undergraduate and graduate students, disseminate, and publish research in peer-reviewed forensic journals. In order to be successful in this position, the ideal candidate will: * Conduct individual and collaborative multidisciplinary research with intersection of forensic science, physics, mathematics, statistics, and computer science. * Develop, validate, and implement programming codes, statistical algorithms, and a database for the comparison of fracture fit?s images. * Supervise graduate and undergraduate students in research. * Assist the PIs writing reports to the funding agency. * Publish high quality peer-reviewed journal articles under the direction of the Principal Investigator (PI). Qualifications * Ph.D. in Physics, Computer Science, Statistics, or a related field with a focus on data imaging. Ph.D. must be earned before the start date of the post, or with verification that will be earned within 3 months of the appointment date. * A minimum of two (2) years of research experience. * Strong experimental background or experience in computer programming skills (e.g., Python, R) and machine learning algorithms * Strong organizational and managerial skills. * Ability to lead undergraduate and graduate students. * Ability to communicate effectively, both orally and in writing, as demonstrated by journal publications, technical reports, and presentations at professional and scientific meetings. How to apply: This position is funded for up to 12 months. To apply, please visit WVU careers at: https://wvu.taleo.net/careersection/wvu_research/jobdetail.ftl?job=16807&tz=GMT-04%3A00&tzname=America%2FNew_York and navigate to the position title listed above. ______________________::::__________________________________________ Prof. Aldo Humberto Romero Fellow American Physical Society Assistant Editor EPJB Member of the Editor Board of ?Materials? Physics and Astronomy Department West Virginia University Phone: (304) 2936317 email: alromero at mail.wvu.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From xavier.hinaut at inria.fr Sat Aug 21 04:15:54 2021 From: xavier.hinaut at inria.fr (Xavier Hinaut) Date: Sat, 21 Aug 2021 10:15:54 +0200 Subject: Connectionists: [meetings] 2nd SMILES workshop, Aug 31st: Sensorimotor Interaction, Language and Embodiment of Symbols Message-ID: <13846920-6238-4C47-8B71-1259E5E959CE@inria.fr> * WHAT The SMILES workshop is about Sensorimotor Interaction, Language and Embodiment of Symbols (SMILES). It is a satellite event from the ICDL 2020 (International Conference on Developmental Learning). * WHEN Tuesday 31st of August 2021. Planned schedule (it might change): 9am - 8.30pm CEST (UTC+2). * WHERE Online event on Zoom. (Link sent to registered people the day before, see LINKS section) * WHO 8 Invited speakers from multiple fields: neurolinguistics, speech communication, language evolution, developmental science, social robotics, computational neuroscience, language acquisition. - Morten Christiansen, Cornell University, NY, USA & Aarhus University, Denmark - Kaya de Barbaro, University of California San Diego, USA - Cynthia Matuszek, University of Maryland, Baltimore County, USA - Yair Lakretz, NeuroSpin Center, Gif sur Yvette, France - Harm Brouwer, Saarland University, Germany - Jean-Luc Schwartz, Gipsa lab, Grenoble-Alpes University, France - Daniel Dor, Tel Aviv University, Israel - Lauren Emberson, University of British Columbia, Canada * LINKS - ** Website **: https://sites.google.com/view/smiles-workshop/home - ** Registration is free but mandatory **: https://forms.gle/tyvMdbb8UJFyXZky8 - Contact: smiles.conf at gmail.com - ICDL conference website: https://icdl-2021.org/ * WHAT+ (Short Description) On the one hand, models of sensorimotor interaction are embodied in the environment and in the interaction with other agents. On the other hand, recent Deep Learning development of Natural Language Processing (NLP) models allow to capture increasing language complexity (e.g. compositional representations, word embedding, long term dependencies). However, those NLP models are disembodied in the sense that they are learned from static datasets of text or speech. How can we bridge the gap from low-level sensorimotor interaction to high-level compositional symbolic communication? The SMILES workshop will address this issue through an interdisciplinary approach involving researchers from (but not limited to): - Sensori-motor learning, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Sensori-motor learning, - Symbol grounding and symbol emergence, - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and acquisition in brains and machines, - Models of animal communication, - Language evolution, - Understanding composition and temporal processing in neural network models, and - Enaction, active perception, perception-action loop. SMILES workshop organisers - Xavier Hinaut, Inria, Bordeaux, France - Cl?ment Moulin-Frier, Inria and Ensta ParisTech, Bordeaux, France - Silvia Pagliarini, Inria, Bordeaux, France - Michael Spranger, Sony AI and Sony CSL, Tokyo, Japan - Tadahiro Taniguchi, Ritsumeikan University, Kyoto, Japan - Anne S. Warlaumont, University of California, Los Angeles, America - Junpei Zhong, Nottingham Trent University, Nottingham, United Kingdom Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Universit? de Bordeaux Institut des Maladies Neurod?g?n?ratives www.xavierhinaut.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From dthakur at cdt.org Fri Aug 20 16:31:14 2021 From: dthakur at cdt.org (Dhanaraj Thakur) Date: Fri, 20 Aug 2021 16:31:14 -0400 Subject: Connectionists: CDT Non-Residential Fellows Program - Call for Applications Message-ID: <10c135dd-4389-ea34-a663-0b5f7f23f2cb@cdt.org> Hi all, The Center for Democracy & Technology is now accepting applications for its 2022 cohort of non-residential Fellows. The Fellows program is a great opportunity for researchers and academics to help inform important tech policy debates and to engage with policy-makers in the US and EU. In addition, new Fellows will be able to participate in ournetwork of non-residential Fellows . We encourage applications from interested persons who will commit to a two-year, nonresident engagement and possess a Ph.D., JD, or equivalent in their respective field of study. These can include but are not limited to public policy, sociology, psychology, computer science, economics, law, etc. Interested applicants should submit a cover letter, including areas of interest and how they are aligned with CDT?s work, resume, and one relevant writing sample which should already be published. To send applications or request further information please contact Jamal Magby at research at cdt.org thanks, Dhanaraj -- *Dhanaraj Thakur* (he/him) | Research Director Center for Democracy & Technology |*cdt.org * *E:* dthakur at cdt.org | *P:*?+1 202 407 8849 | @thakurdhanaraj -------------- next part -------------- An HTML attachment was scrubbed... URL: From christos.dimitrakakis at gmail.com Sat Aug 21 10:22:02 2021 From: christos.dimitrakakis at gmail.com (Christos Dimitrakakis) Date: Sat, 21 Aug 2021 16:22:02 +0200 Subject: Connectionists: PhD position at the university of Neuchatel Message-ID: <653c6056-0302-580c-e324-dd07151068f9@gmail.com> We are looking for a PhD student to join our group on reinforcement learning and decision making at the University of Neuchatel, Switzerland ( https://www.unine.ch/ ).? We are particularly interested in candidates with a strong mathematical background. Prior research experience as documented by your Masters thesis will be an additional bonus. Although any area in the intersection of machine learning, statistics and artificial intelligence may be considered, we are primarily looking for a student with a sincere interest in one or more of the following areas: 1. Reinforcement learning 2. Privacy (e.g. differential privacy) 3. Fairness in machine learning. Examples of our group's past and current research can be found on arxiv: https://arxiv.org/search/?searchtype=author&query=Dimitrakakis%2C+C.? The student will have the opportunity to visit and work with other group members at the University of Oslo, Norway ( https://www.mn.uio.no/ifi/english/people/aca/chridim/index.html ) and Chalmers University of Technology, Sweden ( http://www.cse.chalmers.se/~chrdimi/ ). The position is available from 1 Februrary 2022. For further information, please contact me directly at christos.dimitrakakis at gmail.com with the subject 'PhD Neuchatel'. From mtanveer at iiti.ac.in Sun Aug 22 09:25:11 2021 From: mtanveer at iiti.ac.in (M Tanveer) Date: Sun, 22 Aug 2021 18:55:11 +0530 Subject: Connectionists: Call for Papers - ACM TOMM and IEEE JBHI Message-ID: Dear Colleague, We are organizing a few special issues and look forward to receiving your high-quality submissions. Kindly encourage your group to submit high quality papers and if possible please circulate within your circle. (1) Advanced machine learning algorithms for biomedical data and imaging Journal: IEEE Journal of Biomedical and Health Informatics Editors: M. Tanveer, Chin-Teng Lin, AK Singh Deadline for submissions: November 30, 2021 (2) Deep learning algorithms for multimedia data analytics in industry 4.0 applications Journal: ACM Transactions on Multimedia Computing, Communications, and Applications Editors: M. Tanveer, Chin-Teng Lin, N. Kumar Deadline for submissions: October 30, 2021 Thank you very much. Kind regards, Tanveer ---------------------------------------------------------- Dr. M. Tanveer (General Chair - ICONIP 2022) Associate Professor and Ramanujan Fellow Department of Mathematics Indian Institute of Technology Indore Email: mtanveer at iiti.ac.in Mobile: +91-9413259268 Homepage: http://iiti.ac.in/people/~mtanveer/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From steve at bu.edu Sun Aug 22 15:18:35 2021 From: steve at bu.edu (Grossberg, Stephen) Date: Sun, 22 Aug 2021 19:18:35 +0000 Subject: Connectionists: New articles about consciousness, attention, canonical cortical circuits, hippocampal theta rhythms, and autonomous intelligence In-Reply-To: References: , Message-ID: Dear Colleagues, I have published several integrative articles this year about topics of current interest and have listed them here for your convenience. They are all available Open Access: Grossberg, S. (2021). How does your brain create your conscious mind? Psychology Today, August 17. https://www.psychologytoday.com/us/blog/how-does-brain-make-mind/202108/how-does-your-brain-create-your-conscious-mind Grossberg, S. (2021). Attention: Multiple types, brain resonances, psychological functions, and conscious states. Journal of Integrative Neuroscience. https://jin.imrpress.com/article/2021/1757-448X/JIN2020406.shtml Grossberg, S. (2021). A canonical laminar neocortical circuit whose bottom-up, horizontal, and top-down pathways control attention, learning, and prediction. Frontiers in Systems Neuroscience. Published online: 23 April 2021. https://www.frontiersin.org/articles/10.3389/fnsys.2021.650263/full Grossberg, S. (2021). A neural model of intrinsic and extrinsic hippocampal theta rhythms: Anatomy, neurophysiology, and function. Fronters in Systems Neuroscience. Published online: 28 April 2021. https://www.frontiersin.org/articles/10.3389/fnsys.2021.665052/full Grossberg, S. (2021). Toward autonomous adaptive intelligence: Building upon neural models of how brains make minds. Invited article in 50th Anniversary Special Issue of IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51, 51-75. https://sites.bu.edu/steveg/files/2021/01/tsmc-grossberg-3041476_4.pdf Best, Steve Stephen Grossberg http://en.wikipedia.org/wiki/Stephen_Grossberg http://scholar.google.com/citations?user=3BIV70wAAAAJ&hl=en https://youtu.be/9n5AnvFur7I https://www.youtube.com/watch?v=_hBye6JQCh4 https://www.amazon.com/Conscious-Mind-Resonant-Brain-Makes/dp/0190070552 Wang Professor of Cognitive and Neural Systems Director, Center for Adaptive Systems Professor Emeritus of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering Boston University sites.bu.edu/steveg steve at bu.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From sbminna at gmail.com Sun Aug 22 07:58:11 2021 From: sbminna at gmail.com (Inna S) Date: Sun, 22 Aug 2021 14:58:11 +0300 Subject: Connectionists: Computational neuroscientist position at the Gonda Brain Research Center, Bar-Ilan University In-Reply-To: References: Message-ID: *Faculty Position at the Gonda Brain Research Center, Bar-Ilan University* The Gonda Multidisciplinary Brain Research Center at Bar-Ilan University looking for excellent early-stage scientist for tenure track position (rank commensurate with qualifications and experience) starting in the academic year 2022-2023. The position is open for a candidate with a focus in *computational neuroscience*, including theoretical neuroscience and modelling. All applicants will be evaluated for merit. The appointments are subject to budgetary approval. The Gonda Multidisciplinary Brain Research Center at Bar-Ilan University brings together researchers from a variety of fields essential for understanding the brain, including life sciences, neurophysiology, psychology, linguistics, computer science, mathematics and physics. Research at the Center addresses the brain at all levels - from behavior and cognitive processing through neural circuits, all the way to molecular mechanisms, in health and in disease. Candidates are expected to have a doctorate and post-doctoral training in relevant fields, and to show an excellent track-record for their stage of career. Interested candidates should submit a letter of application, CV and a research statement. For more information, inquiries and applications, please contact Dr. Inna Sukhotinsky (Inna.Sukhotinsky at biu.ac.il). BIU is an equal opportunity employer and all qualified applicants will receive consideration for employment. *Submission deadline:* September 30, 2021 [image: image.jpeg] *Website *www.gondabrain.biu.ac.il *| Facebook *gonda.brain -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.jpeg Type: image/jpeg Size: 92984 bytes Desc: not available URL: From battleday at princeton.edu Mon Aug 23 12:11:26 2021 From: battleday at princeton.edu (Ruairidh McLennan Battleday) Date: Mon, 23 Aug 2021 09:11:26 -0700 Subject: Connectionists: Reminder (one week left): Call for papers: Symposium on Mathematics of Neuroscience Message-ID: Two decades into the 21st century, can we claim to be any closer to a unified model of the brain? In this exploratory symposium, we invite submissions for short talks and posters presenting general mathematical models of brain function. We give priority to those models that account for brain or behavioural data, or provide simulations to that effect. The symposium will be held at the applied mathematics conference ICNAAM 2021, to be held virtually and in person on the island of Rhodes, Greece from the 20-26th of September 2021. Submission is by 250-word abstract before the 30th August, sent to the organizers Prof Dan V. Nicolau Jr ( dan.nicolau at qut.edu.au) and Dr Ruairidh M. Battleday ( battleday at princeton.edu). We already have a great lineup (www.neuromonster.org), and with one week left until the deadline for the abstract submission encourage any remaining interested parties to apply. Ruairidh and Dan -- Dr. Ruairidh McLennan Battleday, BMBCh (Oxon) MA PhD Candidate and Cognitive Science Fellow Computational Cognitive Science Lab, Department of Computer Science Princeton University Department of Statistics St John's College University of Oxford -------------- next part -------------- An HTML attachment was scrubbed... URL: From ieao at colourfig.com Wed Aug 25 01:52:48 2021 From: ieao at colourfig.com (Ifedayo-Emmanuel Adeyefa-Olasupo) Date: Wed, 25 Aug 2021 05:52:48 +0000 Subject: Connectionists: Figbox: what do I gain as postdoc or early career researcher Message-ID: Dear Colleagues, Happy to share with you an updated version of figbox. click here: https://figbox.co/ figbox figbox helps you get quick quality reviews of qualitative or quantitative figures you plan to include in an upcoming submission or presentation from published and experienced researchers. Get the help you need, improve your overall message, advance your career! figbox.co Like to thank everyone who reached out to me and was able to provide comments and suggestions on how to improve the software. Note Figbox was built and is currently maintained by volunteer scholars. Just a quick reminder figbox allow early career researchers (e.g., postdocs) the ability to promote their publications among early career researchers in over 40 different countries around the world. Two, by providing more junior scholars with personalized feedback and content postdocs are awarded mentorship certificates. These verified certificates can support the postdoc?s CV and can potentially boost the postdoc's academic career. Three, junior scholars who are intellectually supported by a postdoc can support the postdoc with cash donations. This helps the postdoc with living expenses such as food and transportation cost. Best Regards, Emmanuel -------------- next part -------------- An HTML attachment was scrubbed... URL: From interdonatos at gmail.com Tue Aug 24 11:52:26 2021 From: interdonatos at gmail.com (Roberto Interdonato) Date: Tue, 24 Aug 2021 17:52:26 +0200 Subject: Connectionists: CFP Complex Networks 2021 (Deadline Sept 01) Message-ID: *10th** International Conference on Complex Networks & Their Applications* Madrid, Spain (online & in-person) -* November 30 - December 02, 2021* COMPLEX NETWORKS 2021 You are cordially invited to submit your contribution until September 01, 2021. *SPEAKERS * ? Marc Barth?l?my CEA France ? Ginestra Bianconi Queen Mary University of London UK ? Jo?o Gama University of Porto Portugal ? Dirk Helbing ETH Z?rich Switzerland ? Yizhou Sun UCLA USA ? Alessandro Vespignani Northeastern University USA *TUTORIALS (November 29, 2021)* ? Elisabeth Lex Graz University of Technology Austria ? Giovanni Petri ISI Foundation Italy *PUBLICATION* Full papers (not previously published up to 12 pages) and Extended Abstracts (about published or unpublished research up to 3 pages) are welcome. ? *Papers *will be included in the conference *proceedings edited by Springer* ? *Extended abstracts* will be published in the *Book of Abstracts (with ISBN)* Templates are available on the submission webpage. If in doubt, please contact the Publication Chair (matteo.zignani at unimi.it) All contributions should be submitted via EasyChair . Extended versions will be invited for publication in *special issues of international journals:* o Applied Network Science edited by Springer o Complex Systems o Computational Social Networks edited by Springer o Network Science edited by Cambridge University Press o PLOS one o Social Network Analysis and Mining edited by Springer *TOPICS* *Topics include, but are not limited to: * o Models of Complex Networks o Structural Network Properties and Analysis o Complex Networks and Epidemics o Community Structure in Networks o Community Discovery in Complex Networks o Motif Discovery in Complex Networks o Network Mining o Network embedding methods o Machine learning with graphs o Dynamics and Evolution Patterns of Complex Networks o Link Prediction o Multilayer Networks o Network Controllability o Synchronization in Networks o Visual Representation of Complex Networks o Large-scale Graph Analytics o Social Reputation, Influence, and Trust o Information Spreading in Social Media o Rumour and Viral Marketing in Social Networks o Recommendation Systems and Complex Networks o Financial and Economic Networks o Complex Networks and Mobility o Biological and Technological Networks o Mobile call Networks o Bioinformatics and Earth Sciences Applications o Resilience and Robustness of Complex Networks o Complex Networks for Physical Infrastructures o Complex Networks, Smart Cities and Smart Grids o Political networks o Supply chain networks o Complex networks and information systems o Complex networks and CPS/IoT o Graph signal processing o Cognitive Network Science o Network Medicine o Network Neuroscience o Quantifying success through network analysis o Temporal and spatial networks o Historical Networks -------------- next part -------------- An HTML attachment was scrubbed... URL: From massimo.srt at gmail.com Wed Aug 25 04:27:33 2021 From: massimo.srt at gmail.com (Massimo Sartori) Date: Wed, 25 Aug 2021 10:27:33 +0200 Subject: Connectionists: [jobs] Two postdoc openings: model-based control of bio-protective robots for injury prevention and movement restoration Message-ID: Do you want to develop wearable robots for preventing musculoskeletal injuries in occupational settings, e.g., factory workers performing manual tasks? Do you want to understand how skeletal muscles change their biological structure in response to mechanical stimuli and how rehabilitation robots (e.g., exoskeletons, robotic dynamometers) can steer such structural changes over time? The Neuro-Mechanical Modeling and Engineering Lab (Department of Biomechanical Engineering, University of Twente) is seeking for two outstanding postdoctoral fellows to work on two large-scale European projects respectively: H2020 ERC project INTERACT: https://cordis.europa.eu/project/id/803035 H2020 RIA project SOPHIA: https://project-sophia.eu Please, apply exclusively via the links below: *Postdoc opening 1 (INTERACT project):* Modeling skeletal muscle adaptation for the control of rehabilitation robots across large temporal scales: Apply here: *https://www.utwente.nl/en/organisation/careers/!/128/ * by September 13, 2021. *Postdoc opening 2 (SOPHIA project):* Computational models of musculoskeletal injury prediction and control of bio-protective exosuits: Apply here: *https://www.utwente.nl/en/organisation/careers/!/127/ * by August 31, 2021. We offer high-reaching positions with a generous allowance as well as extraordinary research facilities and working environment. Your work will be facilitated by in-house expertise and mentorship. You will collaborate with top-scientists on aspects including exoskeleton control, skeletal muscle modelling, statistical modelling, giving large opportunities for growth and to perform impactful research! --- Massimo Sartori, Ph.D. Professor and Chair, Neuromechanical Engineering Director, Neuromechanical Modeling & Engineering Lab University of Twente & TechMed Centre Faculty of Engineering Technology Department of Biomechanical Engineering 7500 AE, The Netherlands Personal Website: https://people.utwente.nl/m.sartori Lab Website: https://bit.ly/NMLab Lab YouTube Channel: https://bit.ly/NMLTube -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.magnuson at bcbl.eu Wed Aug 25 11:04:42 2021 From: j.magnuson at bcbl.eu (James Magnuson) Date: Wed, 25 Aug 2021 17:04:42 +0200 (CEST) Subject: Connectionists: BCBL PhD and postdoc positions with Arty Samuel & Jim Magnuson Message-ID: <1838930877.245396.1629903882664.JavaMail.zimbra@bcbl.eu> Basque Center on Cognition, Brain and Language ( [ https://www.bcbl.eu/en | BCBL ] ): Recruiting Postdocs and PhD students Each of our groups (Jim Magnuson: [ https://www.bcbl.eu/en/research/research-groups/computational-neuroscience | Computational Neuroscience ] ; Arty Samuel: [ https://www.bcbl.eu/en/research/research-groups/spoken-language | Spoken Language ] ) will be recruiting a postdoc and a PhD student in 2022. BCBL provides an exceptional intellectual environment with a large group of scientists investigating spoken and written language. There are state of the art facilities, including a high-powered computing cluster, fMRI, MEG, EEG, eyetracking, and equipment for behavioral experiments. Our groups study spoken language using behavioral, neural, and computational approaches, and interact with other groups that have overlapping interests (e.g., Clara Martin: [ https://www.bcbl.eu/en/research/research-groups/speech-bilingualism | Speech and Bilingualism ] ; Nicola Molinaro: [ https://www.bcbl.eu/en/research/research-groups/brain-rhythms-cognition | Brain Rhythms and Cognition ] ). If you are interested in applying for one of these positions, please contact one or both of us ( [ mailto:j.magnuson at bcbl.eu | j.magnuson at bcbl.eu ] , [ mailto:a.samuel at bcbl.eu | a.samuel at bcbl.eu ] ) -------------- next part -------------- An HTML attachment was scrubbed... URL: From benabbessarra at gmail.com Wed Aug 25 12:04:43 2021 From: benabbessarra at gmail.com (=?UTF-8?Q?Sarra_Ben_Abb=C3=A8s?=) Date: Wed, 25 Aug 2021 18:04:43 +0200 Subject: Connectionists: [CFP] 1st International Workshop on Ontology Uses and Contribution to Artificial Intelligence @ KR-2021 Message-ID: Dear colleagues and researchers, Please consider submitting a paper for the 1st International workshop on "Ontology Uses and Contribution to Artificial Intelligence" which will be held online or in Hanoi, Vietnam - November 6-12, 2021. * **** OnUCAI - CALL FOR PAPERS ***** * Ontology Uses and Contribution to Artificial Intelligence* * 1st International Workshop, in conjunction with *KR 2021 * November 6-12, 2021 - Online or in Hanoi, Vietnam* https://sites.google.com/view/onucai-kr2021 ** Important dates ** - - *Workshop paper submission due:**September 06, 2021* - *Workshop paper notifications: *September 30, 2021 - *Workshop paper camera-ready versions due: *October 12, 2021 - *Workshop registration deadline: *TBA - *Workshop: *November 06-12, 2021 All deadlines are 23:59 anywhere on earth (UTC-12) ** Workshop description ** An ontology is well known to be the best way to represent knowledge in a domain of interest. It is defined by Gruber as ?an explicit specification of a conceptualization?. It allows us to represent explicitly and formally existing entities, their relationships and their constraints in an application domain. This representation is the most suitable and beneficial way to solve many challenging problems related to the information domain (e.g., knowledge representation, knowledge sharing, knowledge reusing, automated reasoning, knowledge capitalizing and ensuring semantic interoperability among heterogeneous systems). Using ontology has many advantages, among them we can cite ontology reusing, reasoning and explanation, commitment and agreement on a domain of discourse, ontology evolution and mapping, etc. As a field of artificial intelligence (AI), ontology aims at representing knowledge based on declarative and symbolic formalization. Combining this symbolic field with computational fields of IA such as Machine Learning (ML), Deep Learning (DL), Probabilistic Graphical Models (PGMs), Computer Vision (CV) and Natural Languages Processing (NLP) is a promising association. Indeed, ontological modeling plays a vital role to help AI reducing the complexity of the studied domain and organizing information inside it. It broadens AI?s scope allowing it to include any data type as it supports unstructured, semi-structured, or structured data format which enables smoother data integration. The ontology also assists AI for interpretation process, learning, enrichment, prediction, semantic disambiguation and discovering of complex inferences. Finally, the ultimate goal of ontologies is the ability to be integrated in a software to make sense of all information. In the last decade, ontologies are increasingly being used to provide background knowledge for several AI domains in different sectors (e.g. energy, transport, health, banking and insurance, etc.). Some of these AI domains are: - Machine learning and deep learning: semantic data selection, semantic data pre-processing, semantic data transformation, semantic data prediction, semantic clustering correction of the outputs, semantic enrichment with ontological concepts, use the semantic structure for promoting distance measure, etc. - Probabilistic Graphical Models: learning PGM (structure or parameters) using ontologies, probabilistic semantic reasoning, semantic causality and probability, etc. - Computer Vision: semantic image processing, semantic image classification, semantic object recognition/classification, etc. - Blockchain: semantic transactions, interoperable blockchain systems, etc. - Natural Language Processing: semantic text mining, semantic text classification, semantic role labelling, semantic machine translation, semantic question answering, ontology based text summarizing, semantic recommendation systems, etc. - Robotics: semantic task composition, task assignment, communication, cooperation and coordination, etc. - Voice-video-speech: semantic voice recognition, semantic speech annotation, etc. - Game Theory: semantic definition of specific games, semantic rules and goals definition, etc. - etc. ** Objective ** This workshop aims at highlighting recent and future advances on the role of ontologies and knowledge graphs in different domains of AI and how it can be used in order to reduce the semantic gap between the data, applications, machine learning process, etc., in order to obtain a semantic-aware approaches. In addition, the goal of this workshop is to bring together an area for experts from industry, science and academia to exchange ideas and discuss results of on-going research in ontologies and AI approaches. We invite the submission of original works that is related -- but are not limited to -- the topics below. ** Topics of interests ** - Ontology for Machine Learning/Deep Learning - Ontology for Probabilistic Graphical Models - Ontology for Federated Machine Learning - Ontology for Smart Contracts - Ontology for Computer Vision - Ontology for Natural Language Processing - Ontology for Robotics and Multi-agent Systems - Ontology for Voice-video-speech - Ontology for Game Theory - and so on. ** Submission ** The workshop is open to submit unpublished work resulting from research that presents original scientific results, methodological aspects, concepts and approaches. All submissions are not anonymous and must be PDF documents written in English and formatted using the following style files: *KR2021_authors_kit * Papers are to be submitted through the workshop's *EasyChair * submission page. We welcome the following types of contributions: - *Full papers* of up to 9 pages, including abstract, figures and appendices (if any), but excluding references and acknowledgements: Finished or consolidated R&D works, to be included in one of the Workshop topics. - *Short papers* of up to 4 pages, excluding references and acknowledgements: Ongoing works with relevant preliminary results, opened to discussion. At least one author of each accepted paper must register for the workshop, in order to present the paper. For further instructions, please refer to the *KR 2021 * page. ** Workshop chairs ** - Sarra Ben Abb?s, Engie, France - Lynda Temal, Engie, France - Nada Mimouni, CNAM, France - Ahmed Mabrouk, Engie, France - Philippe Calvez, Engie, France ** Program Committee ** - Shridhar Devamane, Physical Design Engineer, Tecsec Technologies, Bangalore, India - Philippe Leray, Professor at University of Nantes - Stefan FENZ, key researcher at SBA Research and Senior Scientist at Vienna University of Technology - Olivier Dameron, Professor at Universit? de Rennes I, Dyliss team, Irisa / Inria Rennes-Bretagne Atlantique - Aar?n Ayll?n Benitez, Phd in bioinformatique, ontology leader at BASF digital solutions - Fran?ois Scharffe, Researcher on Knowledge based AI, New York, United States - Maxime Lefran?ois, Associate Professor at Saint Etienne University, France - Pierre Maret, The QA Company & Saint Etienne University, France **Publication* The best papers from this workshop may be included in the supplementary proceedings of KR 2021. -------------- next part -------------- An HTML attachment was scrubbed... URL: From miguel-areias at dcc.fc.up.pt Thu Aug 26 06:03:11 2021 From: miguel-areias at dcc.fc.up.pt (Miguel Areias) Date: Thu, 26 Aug 2021 11:03:11 +0100 Subject: Connectionists: Call for Participation - LP/CP Programming Contest 2021 Message-ID: ========================================================================= ? ? ? ? ? ? ? ? ? ? ? ? ? ?CALL FOR PARTICIPATION ? ? ? ? ? ? ? ? ? ? ? ?LP/CP Programming Contest 2021 ========================================================================= The traditional LP/CP Programming Contest will be run in virtual mode during ICLP 2021. The contest will start on Friday 24 September at 12:00 (midday, UTC+1) and will last 24 hours. Don't miss this opportunity! Join the contest with your favorite declarative programming languages and systems. Show your skills in declarative problem solving. The contest is data agnostic. All problems use easy-to-parse input and output format. You can easily shape them for your preferred system by writing a script. Checkers will be provided to ease the identification of bugs thanks to textual representations of testcases and solutions. Details online: https://github.com/alviano/lpcp-contest-2021 ========================================================================= From kshen at research.baycrest.org Thu Aug 26 14:23:38 2021 From: kshen at research.baycrest.org (Kelly Shen) Date: Thu, 26 Aug 2021 14:23:38 -0400 Subject: Connectionists: =?utf-8?q?Frontiers_Research_Topic_on_=E2=80=9CNe?= =?utf-8?q?uroinformatics_of_Large-Scale_Brain_Modelling=E2=80=9D?= =?utf-8?q?=3A_Abstracts_due_Sep_1?= Message-ID: Dear all, A reminder that the extended abstract deadline for our special issue is September 1st. More below: ***** We are happy to inform you that we have extended the deadline for submissions to the Research Topic, jointly within Frontiers in Neuroinformatics and Frontiers in Computational Neuroscience, on ?Neuroinformatics of Large-Scale Brain Modelling?. This Research Topic will document the various ways in which neuroinformatics approaches are being applied in large-scale brain modelling, informing readers on both established practices and emerging techniques. We seek Original Research, Review, Mini-Review, Hypothesis and Theory, Perspective, and Opinion articles that cover, but are not limited to, the following topics: New, biologically constrained, large-scale brain models and modelling methodologies New approaches to parameter optimization, parameter space exploration, and systematic tracking of simulation behaviour across parameter combinations Informing neural models with genetic and multi-omic data from large-scale databases and individual patients/subjects Systematic computational modelling studies on large numbers of subjects, and/or using large-scale open-access datasets (HCP, ABCD, etc.) ?Hybrid? modelling schemes that combine mean-field with spiking network models ?Hybrid? approaches to defining connectivity in large-scale brain models (e.g. supplementing tractography with microscopy data for higher-resolution subcortical connectivity structure) Simulations using high-resolution neuroanatomical data from initiatives such as BigBrain, Allen Institute, etc. ?High-density? (large number of regions; small parcels) connectome-based neural mass modelling Ontologies, systems, and tools for definition and specification of large-scale neural models Comparisons between detailed spiking/morphological simulations and neural mass model simulations Comparisons between models based on high-resolution and low-resolution Allen atlas connectivities Other neuroinformatics challenges and solutions in large-scale brain simulations Full details can be found on the research topic webpage at: www.frontiersin.org/research-topics/16641/neuroinformatics-of-large-scale-brain-modelling If you are considering submitting, please submit an abstract by 1st Sept 2021. Deadline for submission of full manuscripts is 15th Dec 2021. We look forward to hearing from you and sharing this exciting work with the community. Your Research Topic co-editors, John Griffiths Padraig Gleeson Kelly Shen -- Kelly Shen, PhD Scientific Associate Rotman Research Institute at Baycrest 416-785-2500, x2425 kshen at research.baycrest.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From benoit.frenay at unamur.be Thu Aug 26 08:46:10 2021 From: benoit.frenay at unamur.be (=?UTF-8?B?QmVub8OudCBGcsOpbmF5?=) Date: Thu, 26 Aug 2021 14:46:10 +0200 Subject: Connectionists: Full-time assistant professor in AI at UNamur Message-ID: Dear colleagues, If you are looking for a team of kind and passionate colleagues that value both research and teaching, the Faculty of Computer Science at UNamur has an open academic position in artificial intelligence.? The Faculty is more than 50 years old and is located in Namur, an historical city at the center of Wallonia. We are looking for candidates that will create and contribute to collaborations in line with the Faculty's areas of interest (software engineering, data engineering, data science, artificial intelligence, security, formal methods, modeling?). All details can be found here (deadline is September 12th): * https://euraxess.ec.europa.eu/jobs/650796 * https://jobs.unamur.be/emploi.2021-05-27.7877206869 Best regards, Beno?t Fr?nay -------------- next part -------------- An HTML attachment was scrubbed... URL: From S.Qiu-1 at tudelft.nl Fri Aug 27 09:36:09 2021 From: S.Qiu-1 at tudelft.nl (Sihang Qiu - EWI) Date: Fri, 27 Aug 2021 13:36:09 +0000 Subject: Connectionists: BHCC 2021 - Deadline Extended Message-ID: <3AEEC06B-3DEF-4683-88AF-1675BCD1001F@tudelft.nl> --- Apologies for cross-posting --- Third Symposium on Biases in Human Computation and Crowdsourcing (BHCC 2021) The deadline for contributions to BHCC2021 has been extended to September 23. Website: https://www.bhcc-symposium.com/ 10 - 12 November 2021, Delft, Netherlands (Online) BHCC 2021 is an event of the Academic Fringe Festival Organized by TU Delft and CHI Nederland *Important Dates* Time zone: Anywhere on Earth (AoE) - Full Papers and Short papers due: 23 September 2021 - Abstracts due: 23 September 2021 - Notifications: 22 October 2021 - Conference: 10-12 November 2021 *Overview* The goal of this symposium is to analyse both existing human biases in hybrid systems, and methods to manage bias via crowdsourcing and human computation. We will discuss different types of biases, measures and methods to track bias, as well as methodologies to prevent and solve bias. We welcome the submission of research papers and abstracts which describe original work that has not been submitted or currently under review, has not been previously published nor accepted for publication elsewhere, in any other journal or conference. We welcome the submission of the following types of contributions: - Full papers should be at most 10 pages in length (including figures, tables, appendices, and references), - Short papers should be at most 5 pages in length (including figures, tables, appendices, and references), - Abstracts should contain just a title and the abstract, and should detail demos or relevant work or ideas which are under development. They can not contain references. More details: https://www.bhcc-symposium.com/submission *Submission* We implement a double-blind review process. Submissions must be anonymous and the submission must be made via EasyChair: https://easychair.org/conferences/?conf=bhcc2021 We are committed to create an equal opportunity environment, without regard to race, gender identity or expression, age, disability, or any other status. For this reason, if you feel that you are in a disadvantaged situation or you require assistance please reach out to us (bhcc2021 at easychair.org). We?ll be more than happy to help and allow everyone to submit a paper. We are keen to create a fair working environment for the crowd workers and annotators. For this reason, each submission should clearly state the policies implemented to pursue this aim; each paper should be clear about the amount of work required for an annotator to submit the task, the payment, the time spent by the annotators to finish the task, and all the relevant details aimed at making clear that workers and annotators obtained a fair compensation and treatment for their work. From xavier.hinaut at inria.fr Fri Aug 27 05:26:18 2021 From: xavier.hinaut at inria.fr (Xavier Hinaut) Date: Fri, 27 Aug 2021 11:26:18 +0200 Subject: Connectionists: 2nd SMILES workshop, Aug 31st: Sensorimotor Interaction, Language and Embodiment of Symbols Message-ID: <49DF4C7C-2962-4335-97F0-640D44950110@inria.fr> * WHAT The SMILES workshop is about Sensorimotor Interaction, Language and Embodiment of Symbols (SMILES). It is a satellite event from the ICDL 2020 (International Conference on Developmental Learning). * WHEN Tuesday 31st of August 2021. Planned schedule: 9am - 8.30pm CEST (UTC+2). * WHERE Online event on Zoom. (Link sent to registered people the day before, see LINKS section) * WHO 8 Invited speakers from multiple fields: neurolinguistics, speech communication, language evolution, developmental science, social robotics, computational neuroscience, language acquisition. - Morten Christiansen, Cornell University, NY, USA & Aarhus University, Denmark - Kaya de Barbaro, University of California San Diego, USA - Cynthia Matuszek, University of Maryland, Baltimore County, USA - Yair Lakretz, NeuroSpin Center, Gif sur Yvette, France - Harm Brouwer, Saarland University, Germany - Jean-Luc Schwartz, Gipsa lab, Grenoble-Alpes University, France - Daniel Dor, Tel Aviv University, Israel - Lauren Emberson, University of British Columbia, Canada - Bart de Boer, AI-lab, Vrije Universiteit Brussel, Belgium * LINKS - ** Website **: https://sites.google.com/view/smiles-workshop/home - ** Registration is free but mandatory **: https://forms.gle/tyvMdbb8UJFyXZky8 - Contact: smiles.conf at gmail.com - ICDL conference website: https://icdl-2021.org/ * WHAT+ (Short Description) On the one hand, models of sensorimotor interaction are embodied in the environment and in the interaction with other agents. On the other hand, recent Deep Learning development of Natural Language Processing (NLP) models allow to capture increasing language complexity (e.g. compositional representations, word embedding, long term dependencies). However, those NLP models are disembodied in the sense that they are learned from static datasets of text or speech. How can we bridge the gap from low-level sensorimotor interaction to high-level compositional symbolic communication? The SMILES workshop will address this issue through an interdisciplinary approach involving researchers from (but not limited to): - Sensori-motor learning, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Sensori-motor learning, - Symbol grounding and symbol emergence, - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and acquisition in brains and machines, - Models of animal communication, - Language evolution, - Understanding composition and temporal processing in neural network models, and - Enaction, active perception, perception-action loop. SMILES workshop organisers - Xavier Hinaut, Inria, Bordeaux, France - Cl?ment Moulin-Frier, Inria and Ensta ParisTech, Bordeaux, France - Silvia Pagliarini, Inria, Bordeaux, France - Michael Spranger, Sony AI and Sony CSL, Tokyo, Japan - Tadahiro Taniguchi, Ritsumeikan University, Kyoto, Japan - Anne S. Warlaumont, University of California, Los Angeles, America - Junpei Zhong, Nottingham Trent University, Nottingham, United Kingdom Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Universit? de Bordeaux Institut des Maladies Neurod?g?n?ratives www.xavierhinaut.com From gros at itp.uni-frankfurt.de Fri Aug 27 12:07:47 2021 From: gros at itp.uni-frankfurt.de (Claudius Gros) Date: Fri, 27 Aug 2021 18:07:47 +0200 Subject: Connectionists: =?utf-8?q?PhD_position_at_the_Goethe_University_F?= =?utf-8?q?rankfurt=2C_Germany?= Message-ID: <38e-61290e00-155-64e52180@233753867> Applications are invited for a fully funded PhD position at the Institute for Theoretical Physics, Goethe University Frankfurt, Germany Fields: complex systems theory, Covid-19 modelling Application deadline: Oct 15, 2021 Supervisor: Prof. Dr. Claudius Gros We are developing new models and generative principles for the societies of interacting agents using a range of toolsets from dynamical systems theory and game theory. Examples are Covid-19 modelling and the influence of envy on the structure of human societies. We are also developing operating principles for reference robot systems, and for neuroscience applications. It is expected that applicants study the publication list available on the website of the lab, as given below. Several subjects are available for the announced PhD thesis, depending on the background of the successful candidate. The work will include analytical investigations and numerical simulations. The candidates should have a Diploma/Master in physics with an excellent academic track record and good computational skills. Experience or strong interest in the fields of complex systems, dynamical systems theory, game theory and/or artificial or biological cognitive systems is expected. The degree of scientific research experience is expected to be on the level of a German Diploma/Master. The appointment will start early 2022, for three years. Interested applicants should submit a curriculum vitae and a list of publications, and arrange for letters of reference to be sent to the address below. Prof. Claudius Gros Institute for Theoretical Physics Goethe University Frankfurt Max-von-Laue-Str. 1 60438 Frankfurt am Main, Germany cgr at itp.uni-frankfurt.de http://www.itp.uni-frankfurt.de/~gros General information on the University of Frankfurt and its employment policy: With its around 46,000 students and 4,600 employees, the Goethe University in Frankfurt is the largest university in the state of Hessen and an internationally renowned, important regional employer. Numerous quality and performance oriented internal reforms have been initiated in the recent years. The reorganized campuses for natural sciences and humanities offer an ideal environment for research and education. Since 2008, the Goethe University is a foundation under public law and enjoys full administrative autonomy. The fixed-term employment of the academic staff is subject to the provisions of the Temporary Science Employment Law and the Hessian Higher Education Act. The University advocates gender equality and therefore strongly encourages women to apply. People with disabilities are given preference if equally qualified. -- ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ### From elmead at ualr.edu Fri Aug 27 18:58:23 2021 From: elmead at ualr.edu (Esther Mead) Date: Fri, 27 Aug 2021 17:58:23 -0500 Subject: Connectionists: CFP - DEVIANCE 2021 Workshop on Deviant Activities on Social Media Co-located with 2021 IEEE Conference on Big Data (IEEE BigData 2021) December 15-18, 2021 Message-ID: DEVIANCE 2021 Workshop on Deviant Activities on Social Media Co-located with 2021 IEEE Conference on Big Data (IEEE BigData 2021) December 15-18, 2021 (due to COVID-19 the workshop will be held virtually) Website: http://cosmos.ualr.edu/workshops/deviance/2021/ Introduction: With the proliferation of smart devices, mobile applications, and social network platforms, the social side effects of these technologies have become more profound, especially in social and political disintegration. Several journalistic and academic investigations have reported that modern communication platforms such as social media (e.g., Twitter, Facebook, blogs, YouTube, and the ?deep web? channels) are strategically used to coordinate various deviant activities such as cyber propaganda campaigns. Several researchers have studied these deviant activities and identified various tactics, techniques, and procedures used by various online deviant groups, e.g., online propagandist groups,terrorist groups sympathizers, black-hat hacker groups, and internet trolls. Various social media platforms utilized the research findings to detect and curb some of these deviant activities. However, the techniques that are used by the aforementioned deviant groups evolve and adapt to go on undetected. This is a growing problem on social media that needs to be explored and solved. In this workshop, our aim is to have a scientific discussion among the experts who study deviant activities on social media, including but not limited to, detection of deviant/disruptive behaviors on social media; misinformation detection, identification, and dissemination; case studies of misinformation; etc. This includes, but is not limited to, the following topics: Research Topics: - Misinformation detection - Misinformation dissemination tactics such as misdirection, hashtag-latching, smoke screening - Multiple platform orchestration (cross-platform dissemination strategies) - Algorithmic manipulation such as exploiting recommendation algorithm bias manipulation - Deviant behaviors on social media platforms such as cyber bullying, organized hacking - Spamming, spear phishing through social media channels - Coordination strategies and detection - Mobs such as cyber flash mobs, smart mobs, deviant cyber flash mobs, automated deviant mobs - Coordinated inauthentic behaviors - Machine driven communications (bots, botnets, social bots, etc.) - Troll detection and strategies - Hate speech (toxic, polarizing, or disruptive content) - Narratives analysis during misinformation online campaigns - Stance detection and intent classification - Policy implications **In the light of recent elections worldwide, the COVID-19 pandemic, and covid-related deviant behaviors such as anti-lockdown campaigns, vaccine hesitancy, etc., we also solicit papers focused on disinformation and misinformation being disseminated related to these events.** Important Dates: Submission Deadline: September 10, 2021 Notification to Authors: October 29, 2021 Camera Ready Due: November 12, 2021 Venue Information: Due to the current COVID-19 pandemic, it is decided that the IEEE BigData conference and the DEVIANCE 2021 Workshop will be held virtually. Further information will be provided closer to the workshop. Submission: Full paper manuscripts must be in English with a maximum length of 10 pages (using the IEEE two-column template). Submissions should be in PDF and include the title, author(s), affiliation(s), e-mail address(es) and abstract on the first page. Workshop papers can be submitted through the submission portal . Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines . All papers accepted for the workshop will be included in the Conference Proceedings published by the IEEE Computer Society Press. Special Issue: Selected presentations will be invited to submit extended studies to Springer?s Social Network Analysis and Mining (SNAM) special issue on Deviant Behaviors on Social Media . Workshop Chairs: Esther Ledelle Mead Postdoctoral Research Fellow, COSMOS Center, UA Little Rock elmead at ualr.edu Muhammad Nihal Hussain Lead Data Scientist, Equifax Inc. mnhussain at ualr.edu Kiran Kumar Bandeli Data Scientist, Walmart Inc. KiranKumar.Bandeli at walmart.com Samer Al-khateeb Assistant Professor, Creighton University SamerAl-Khateeb1 at creighton.edu Nitin Agarwal Jerry L. Maulden-Entergy Chair & Distinguished Professor Director, COSMOS Center, UA Little Rock nxagarwal at ualr.edu Web Chair: Thomas Marcoux Computer & Information Science PhD candidate - COSMOS Center, UA Little Rock txmarcoux at ualr.edu -- Esther Ledelle Mead, PhD Postdoctoral Research Fellow, Collaboratorium for Social Media and Online Behavioral Studies (COSMOS) Information Science, College of Engineering and Information Technology University of Arkansas at Little Rock -------------- next part -------------- An HTML attachment was scrubbed... URL: From vcutsuridis at gmail.com Sat Aug 28 01:31:54 2021 From: vcutsuridis at gmail.com (Vassilis Cutsuridis) Date: Sat, 28 Aug 2021 06:31:54 +0100 Subject: Connectionists: Permanent job in Paris' eye tracking start-up (ORASIS-EAR) Message-ID: *Job Description * *Permanent contract job offer in Paris, Health Sector * *Software Engineer Develop C ++ / C # (M / F) * Orasis-ear is a young dynamic start-up whose mission is to revolutionize the detection of eye movement problems affecting school learning. Two million children are affected in France, including dyslexics. These problems are largely under-detected. The faster detected and re-trained, the better students can advance with school learning You will report directly to the CEO, Z. Kapoula, Research Director at CNRS and founder of the startup. If you are interested in the mission, and you are ready to discover the world of neuro-visual health, eye tracking, and gain skills, do not hesitate to apply. *Goals : * Development of eye movement capture software (eyetracking, accelerometers), of software for eye movement analytics, of visual stimulation software on the REMOBI embedded tablet (in C ++ / C # and Qt). Design, Architecture, Ergonomics and Documentation Maintenance of technical solutions deployed in the cloud, data storage, data management and privacy. *Environment : * Dynamic team, a mix of youth and solid scientific research and business experiences, located in Paris 6th district. Possible trips to IdF France for customer contacts. *Required Skills : * Mastery of C ++ and C # development languages, knowledge of Qt, notions of UI / UX French / English and more *An advantage : * Interest in the health / biomedical field, passionate about Innovation, the brain and eye movements B permit *Desired profile:* Good adaptability, intellectual curiosity, and interest in the field of health and vision. Industrial experience 2 years or more *Starting date: * position to be filled immediately. *Salary: * to be defined according to profile. *Opportunity:* participation in the development of an innovative and very promising CNRS spin-off. For more information, send CV and cover letter to: zoi.kapoula at gmail.com --- Vassilis Cutsuridis, PhD, M.Sc, M.A. School of Computer Science University of Lincoln UK Tel: +44 (0) 1522 83 5701 Email: vcutsuridis at lincoln.ac.uk Web:http://staff.lincoln.ac.uk/vcutsuridis Personal website:http://www.vassiliscutsuridis.org/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From junfeng989 at gmail.com Thu Aug 26 22:15:44 2021 From: junfeng989 at gmail.com (Jun Feng) Date: Fri, 27 Aug 2021 10:15:44 +0800 Subject: Connectionists: CFP: IEEE DependSys/SmartCity-2021, Dec. 17-19, Haikou, China [Submission Deadline: Sep. 1][10+ Special Issues] Message-ID: IEEE DependSys 2021: The 7th IEEE International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications http://www.ieee-cybermatics.org/2021/dependsys/ IEEE SmartCity 2021: The 19th IEEE International Conference on Smart City http://www.ieee-cybermatics.org/2021/smartcity/ The IEEE DependSys/SmartCity 2021 Conferences will be held at Haikou, China, December 17-19, 2021. We will be pretty happy to see all authors manage to attend DependSys/SmartCity-2021. However, given the COVID-19 pandemic and associated travel restrictions, as the safety of people is of the highest priority, we know that special circumstances are best handled by having flexible options, and thus we are offering the option of either physical presence or virtual participation. Please consider to contribute and submit your original research papers to DependSys/SmartCity-2021. ============================================================================= IEEE DependSys/SmartCity 2021 are sponsored by IEEE, IEEE Computer Society, and IEEE Technical Committee on Scalable Computing (TCSC). All accepted papers will be submitted to IEEE Xplore and Engineering Index (EI). Best Paper Awards will be presented to high quality papers. Distinguished papers, after further revisions, will be published in 10+ SCI & EI indexed prestigious journals (confirmed). 1. IEEE Transactions on Intelligent Transportation Systems SI on Graph-based Machine Learning for Intelligent Transportation Systems https://ad051eeb-2ac9-4983-9271-c88f64105e50.filesusr.com/ugd/eaf218_db671bf4e4eb4a41ac1cf6da14a77750.pdf 2. IEEE Transactions on Intelligent Transportation Systems SI on Data Science for Cooperative Intelligent Transportation Systems https://ad051eeb-2ac9-4983-9271-c88f64105e50.filesusr.com/ugd/eaf218_de7a6f420a2b4c6d894e4de63e495624.pdf 3. IEEE Transactions on Network Science and Engineering SI on The Nexus Between Edge Computing and AI for 6G Networks https://www.comsoc.org/publications/journals/ieee-tnse/cfp/nexus-between-edge-computing-and-ai-6g-networks 3. IEEE/ACM Transactions on Computational Biology and Bioinformatics SI: Deep Learning-Empowered Big Data Analytics in Biomedical Applications and Digital Healthcare https://www.computer.org/digital-library/journals/tb/call-for-papers-special-issue-on-deep-learning-empowered-big-data-analytics-in-biomedical-applications-and-digital-healthcare 5. Security and Communication Networks SI on Protocols, Technologies, and Infrastructures for Secure Mobile Video Communications https://www.hindawi.com/journals/scn/si/926306/ 6. MDPI Sensors SI on Recent Advances in Algorithm and Distributed Computing for the Internet of Things https://www.mdpi.com/journal/sensors/special_issues/Algorithm_Distributed_Computing_IOT 7. International Journal of Distributed Sensor Networks SI: Privacy-Preserving Solutions in the Internet of Things https://journals.sagepub.com/page/dsn/collections/special-issues/privacy-preserving-solutions-in-the-internet-of-things 8. IET Communications SI on Intelligent Metasurfaces for Smart Connectivity https://digital-library.theiet.org/files/IET_COM_CFP_IMSC.pdf 9. Building and Environment SI: AI and IoT Applications of Smart Buildings and Smart Environment Design, Construction and Maintenance https://www.journals.elsevier.com/building-and-environment/call-for-papers/ai-and-iot-applications-of-smart-buildings-and-smart-environment-design-construction-and-maintenance 10. Journal of Systems Architecture SI: Cloud-Edge-End Architecture for Internet of Things Applications https://www.journals.elsevier.com/journal-of-systems-architecture/call-for-papers/special-issue-on-cloud-edge-end-architecture-for-internet-of-things-applications-vsi-cloud-edge-end-iot 11. Information SI: "Crossing ?Data, Information, Knowledge, and Wisdom? Models?Challenges, Solutions, and Recommendations" https://www.mdpi.com/journal/information/special_issues/DIKW_RA_2021 * More special issues will be added later. http://www.ieee-cybermatics.org/2021/dependsys/special.html ================== Important Dates ================== Paper Submission Deadline: 1 September, 2021 Authors Notification: 1 October, 2021 Final Manuscript Due: 1 November, 2021 Conference Date: 17-19 December, 2021 ================== Paper Submission ================== All papers need to be submitted electronically through the conference submission website (http://www.ieee-cybermatics.org/2021/dependsys/) with PDF format. The materials presented in the papers should not be published or under submission elsewhere. Each paper is limited to 8 pages (or 10 pages with over length charge) including figures and references using IEEE Computer Society Proceedings Manuscripts style (two columns, single-spaced, 10 fonts). You can confirm the IEEE Computer Society Proceedings Author Guidelines at the following web page: http://www.computer.org/web/cs-cps/ Manuscript Templates for Conference Proceedings can be found at: https://www.ieee.org/conferences_events/conferences/publishing/templates.html Once accepted, the paper will be included into the IEEE conference proceedings published by IEEE Computer Society Press (indexed by EI). At least one of the authors of any accepted paper is requested to register the paper at the conference. -- Dr. Jun Feng Huazhong University of Science and Technology Mobile: +86-18827365073 WeChat: junfeng10001000 E-Mail: junfeng989 at gmail.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From jiangdm at nwpu.edu.cn Thu Aug 26 23:28:40 2021 From: jiangdm at nwpu.edu.cn (=?UTF-8?B?6JKL5Yas5qKF?=) Date: Fri, 27 Aug 2021 11:28:40 +0800 (GMT+08:00) Subject: Connectionists: ACM ICMI 2021: Announcing Blue Sky Paper Awards Message-ID: <7d5bce6f.17771.17b85a702de.Coremail.jiangdm@nwpu.edu.cn> Announcing Blue Sky Paper Awards *************************************** ACM ICMI 2021: Announcing Blue Sky Paper Awards https://icmi.acm.org/2021/index.php?id=award 18-22 Oct 2021, Montreal, Canada *************************************** Announcing New ACM ICMI 2021 Blue Sky Paper Awards The Blue Sky Paper Awards have been announced. Congratulations to awardees! The papers will be presented at ICMI 2021, in the Blue Sky Papers session moderated by Prof. Sharon Oviatt. The tentative conference program is available at https://icmi.acm.org/2021/index.php?id=program First Place: Sandy Pentland Optimized Human-A.I. Group Decision Making: A Personal View Second Place: Georgios Rizos Towards Sonification in Multimodal and User-Friendly Explainable Artificial Intelligence Third Place: Philippe Palanque Dependability and Safety: Two Clouds in the Blue Sky of Multimodal Interaction The Blue Sky paper track at ACM ICMI 2021 emphasizes innovative, visionary, and highimpact contributions. This track solicited papers relevant to ICMI content that go beyond the usual research paper to present new visions that stimulate the community to pursue innovative new research directions. The papers were encouraged to present high-risk controversial ideas that may challenge existing assumptions and methodologies, or propose new applications or theories. Submitted papers were expected to represent deep reflection, to argue rigorously, and to present ideas from a high-level synthetic viewpoint (e.g., multidisciplinary, based on multiple methodologies). The 23rd ACM International Conference on Multimodal Interaction (ICMI 2021) will be held in Montreal, Canada October 18-22, 2021. ICMI is the premier international forum for multidisciplinary research on multimodal human-human and human-computer interaction, interfaces, and system development. The main conference themes in 2021 will be behavioral health and virtual connectivity, but other major topics of central interest include human communication and multimodal language/dialogue processing, human-robot/agent interaction, affective computing and social interaction, cognitive modeling, multimodal representations and fusion-based architectures, machine learning for multimodal interaction and system applications, speech, gesture, haptics, olfaction, gaze and vision, multimodal datasets and platforms, mobile and ubiquitous interfaces, interfaces for virtual/augmented reality, smart environments, and assistive technologies. ------------------------------------------------------------------------------- Dongmei Jiang Professor, School of Computer Science, Northwestern Polytechnical University Xi'an China. Tel: +86-29-88431532 Email: jiangdm at nwpu.edu.cn ------------------------------------------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From junfeng989 at gmail.com Sat Aug 28 20:06:04 2021 From: junfeng989 at gmail.com (Jun Feng) Date: Sun, 29 Aug 2021 08:06:04 +0800 Subject: Connectionists: [Deadline Approaching: Sep. 1][10+ Journal Special Issues] CFP IEEE DependSys 2021: The 7th IEEE International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications Message-ID: CFP IEEE DependSys 2021 The 7th IEEE International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications Dec. 17-19, Haikou, China [Submission Deadline: Sep. 1][10+ Journal Special Issues] http://www.ieee-cybermatics.org/2021/dependsys/ IEEE DependSys 2021 conference is the 7th event in the series of conferences which offers a timely venue for bringing together new ideas, techniques, and solutions for dependability and its issues in sensor, cloud, and big data systems and applications. As we are deep into the Information Age, huge amounts of data are generated every day from sensors, individual archives, social networks, Internet of Things, enterprises and Internet in various scales and format which will pose a major challenge to the dependability of our designed systems. As these systems often tend to become inert, fragile, and vulnerable after a period of running. Effectively improving the dependability of sensor, cloud, big data systems and applications has become increasingly critical. This conference provides a forum for individuals, academics, practitioners, and organizations who are developing or procuring sophisticated computer systems on whose dependability of services they need to place great confidence. Future systems need to close the dependability gap in face of challenges in different circumstances. The emphasis will be on differing properties of such services, e.g., continuity, effective performance, real-time responsiveness, ability to overcome data fault, corruption, anomaly, ability to avoid catastrophic failures, prevention of deliberate privacy intrusions, reliability, availability, sustainability, adaptability, heterogeneity, security, safety, and so on. ============================================================================= IEEE DependSys 2021 is sponsored by IEEE, IEEE Computer Society, and IEEE Technical Committee on Scalable Computing (TCSC). All accepted papers will be submitted to IEEE Xplore and Engineering Index (EI). Best Paper Awards will be presented to high quality papers. Distinguished papers, after further revisions, will be published in 10+ SCI & EI indexed prestigious journals (confirmed). 1. IEEE Transactions on Intelligent Transportation Systems SI on Graph-based Machine Learning for Intelligent Transportation Systems https://ad051eeb-2ac9-4983-9271-c88f64105e50.filesusr.com/ugd/eaf218_db671bf4e4eb4a41ac1cf6da14a77750.pdf 2. IEEE Transactions on Intelligent Transportation Systems SI on Data Science for Cooperative Intelligent Transportation Systems https://ad051eeb-2ac9-4983-9271-c88f64105e50.filesusr.com/ugd/eaf218_de7a6f420a2b4c6d894e4de63e495624.pdf 3. IEEE Transactions on Network Science and Engineering SI on The Nexus Between Edge Computing and AI for 6G Networks https://www.comsoc.org/publications/journals/ieee-tnse/cfp/nexus-between-edge-computing-and-ai-6g-networks 3. IEEE/ACM Transactions on Computational Biology and Bioinformatics SI: Deep Learning-Empowered Big Data Analytics in Biomedical Applications and Digital Healthcare https://www.computer.org/digital-library/journals/tb/call-for-papers-special-issue-on-deep-learning-empowered-big-data-analytics-in-biomedical-applications-and-digital-healthcare 5. Security and Communication Networks SI on Protocols, Technologies, and Infrastructures for Secure Mobile Video Communications https://www.hindawi.com/journals/scn/si/926306/ 6. MDPI Sensors SI on Recent Advances in Algorithm and Distributed Computing for the Internet of Things https://www.mdpi.com/journal/sensors/special_issues/Algorithm_Distributed_Computing_IOT 7. International Journal of Distributed Sensor Networks SI: Privacy-Preserving Solutions in the Internet of Things https://journals.sagepub.com/page/dsn/collections/special-issues/privacy-preserving-solutions-in-the-internet-of-things 8. IET Communications SI on Intelligent Metasurfaces for Smart Connectivity https://digital-library.theiet.org/files/IET_COM_CFP_IMSC.pdf 9. Building and Environment SI: AI and IoT Applications of Smart Buildings and Smart Environment Design, Construction and Maintenance https://www.journals.elsevier.com/building-and-environment/call-for-papers/ai-and-iot-applications-of-smart-buildings-and-smart-environment-design-construction-and-maintenance 10. Journal of Systems Architecture SI: Cloud-Edge-End Architecture for Internet of Things Applications https://www.journals.elsevier.com/journal-of-systems-architecture/call-for-papers/special-issue-on-cloud-edge-end-architecture-for-internet-of-things-applications-vsi-cloud-edge-end-iot 11. Information SI: "Crossing ?Data, Information, Knowledge, and Wisdom? Models?Challenges, Solutions, and Recommendations" https://www.mdpi.com/journal/information/special_issues/DIKW_RA_2021 * More special issues will be added later. ================== Important Dates ================== Workshop Proposal Due: 1 August, 2021 Paper Submission Deadline: 1 September, 2021 Authors Notification: 1 October, 2021 Final Manuscript Due: 1 November, 2021 Conference Date: 17-19 December, 2021 ================== Topics of interest include, but are not limited to ================== Track 1: Dependability and Security Fundamentals and Technologies - Concepts, theory, principles, standardization and modelling, and methodologies - Dependability of sensor, wireless, and Ad-hoc networks, software defined networks - Dependability issues in cloud/fog/edge - Security and privacy - Security/privacy in cloud/fog/edge - Homomorphic encryption, differential privacy - Blockchain security - Artificial intelligence - Big data foundation and management - Dependable IoT supporting technologies Track 2: Dependable and Secure Systems - Dependable sensor systems - Dependability and availability issues in distributed systems - Cyber-physical systems (e.g. automotive, aerospace, healthcare, smart grid systems) - Database and transaction processing systems - Safety and security in distributed computing systems - Self-healing, self-protecting, and fault-tolerant systems - Dependability in automotive systems - Dependable integration - Dependability in big data systems - Software system security Track 3: Dependable and Secure Applications - Sensor and robot applications - Big data applications - Cloud/fog/edge applications - Datacenter monitoring - Safety care, medical care and services - Aerospace, industrial, and transportation applications - Energy, smart grid, IoT, CPS, smart city, and utility applications - Decentralized applications, federated learning applications - Mobile sensing applications, detection and tracking Track 4: Dependability and Security Measures and Assessments - Dependability metrics and measures for safety, trust, faith, amenity, easiness, comfort, and worry - Levels and relations, assessment criteria and authority - Dependability measurement, modeling, evaluation, and tools - Dependability evaluation - Software and hardware reliability, verification and validation - Evaluations and tools of anomaly detection and protection in sensor, cloud, big data systems ================== Paper Submission ================== All papers need to be submitted electronically through the conference submission website (https://edas.info/N28864) with PDF format. The materials presented in the papers should not be published or under submission elsewhere. Each paper is limited to 8 pages (or 10 pages with over length charge) including figures and references using IEEE Computer Society Proceedings Manuscripts style (two columns, single-spaced, 10 fonts). You can confirm the IEEE Computer Society Proceedings Author Guidelines at the following web page: http://www.computer.org/web/cs-cps/ Manuscript Templates for Conference Proceedings can be found at: https://www.ieee.org/conferences_events/conferences/publishing/templates.html Once accepted, the paper will be included into the IEEE conference proceedings published by IEEE Computer Society Press (indexed by EI). At least one of the authors of any accepted paper is requested to register the paper at the conference. ================== Organizing Committee ================== General Chairs - Stephen S. Yau, Arizona State University, USA - Zheng Yan, Xidian University, China and Aalto University, Finland - Willy Susilo, University of Wollongong, Australia Program Chairs - Bin Song, Xidian University, China - Mamoun Alazab, Charles Darwin University, Australia - Jun Feng, Huazhong University of Science and Technology, China Steering Committee - Jie Wu, Temple University, USA (Chair) - Md Zakirul Alam Bhuiyan, Fordham University, USA (Chair) - Guojun Wang, Guangzhou University, China - Vincenzo Piuri, University of Milan, Italy - Jiannong Cao, Hong Kong Polytechnic University, Hong Kong - Laurence T. Yang, St. Francis Xavier University, Canada - Sy-Yen Kuo, National Taiwan University, Taiwan - Yi Pan, Georgia State University, USA - A. B. M Shawkat Ali, The University of Haikou, China, Haikou, China - Mohammed Atiquzzaman, University of Oklahoma, USA - Al-Sakib Khan Pathan, Southeast University, Bangladesh - Kenli Li, Hunan University, China - Shui Yu, University of Technology Sydney (UTS), Australia - Yang Xiang, Swinburne University of Technology, Australia - Kim-Kwang Raymond Choo, The University of Texas at San Antonio, USA - Kamruzzaman Joarder, Federation University and Monash University, Australia -- Dr. Jun Feng Huazhong University of Science and Technology Mobile: +86-18827365073 WeChat: junfeng10001000 E-Mail: junfeng989 at gmail.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From boubchir at ai.univ-paris8.fr Wed Aug 25 13:34:09 2021 From: boubchir at ai.univ-paris8.fr (Larbi Boubchir) Date: Wed, 25 Aug 2021 19:34:09 +0200 Subject: Connectionists: [CfP] The 2nd international workshop on Machine Learning for EEG Signal Processing (MLESP) In-Reply-To: References: Message-ID: <264a0b9b-3722-4435-b4d2-12d048c49348@ai.univ-paris8.fr> *CALL FOR PAPERS* The 2^nd international workshop on Machine Learning for EEG Signal Processing (MLESP 2021, https://mlesp2021.sciencesconf.org/) will be held online, from 9 to 12 december 2021, in conjunction with the IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2021, https://ieeebibm.org/BIBM2021/) *Overview* EEG signal processing involves the analysis and treatment of the electrical activity of the brain measured with Electroencephalography, or EEG, in order to provide useful information on which decisions can be made. The recent advances in signal processing and machine learning for EEG data processing have brought an impressive progress to solve several practical and challenging problems in many areas such as healthcare, biomedicine, biomedical engineering, BCI and biometrics. The aim of this workshop is to present and discuss the recent advances in machine learning for EEG signal analysis and processing. We are inviting original research work, as well as significant work-in-progress, covering novel theories, innovative methods, and meaningful applications that can potentially lead to significant advances in EEG data analytics. This workshop is an opportunity to bring together academic and industrial scientists to discuss the recent advances. The topics of interest include but not limited to: - EEG signal processing and analysis - Time-frequency EEG signal analysis - Signal processing for EEG Data - EEG feature extraction and selection - Machine learning for EEG signal processing - EEG classification and Hierarchical clustering - EEG abnormalities detection (e.g. Epileptic seizure, Alzheimer's disease, etc.) - Machine learning in EEG Big Data - Deep Learning for EEG Big Data - Neural Rehabilitation Engineering - Brain-Computer Interface - Neurofeedback - EEG-based Biometrics - Related applications Important Dates Aug. 28, 2021 (11:59 pm CST): Due date for full workshop papers submission Oct 25, 2021: Notification of paper acceptance to authors Nov. 15, 2021: Camera-ready of accepted papers Dec 3-6, 2021: Workshops Paper Submission - Please submit a full-length paper (up to 8 page IEEE 2-column format) through the online submission system. You can download the format instruction here: http://www.ieee.org/conferences_events/conferences/publishing/templates.html - Electronic submissions in PDF format are required. Online Submission https://wi-lab.com/cyberchair/2021/bibm21/index.php Publication All accepted papers will be published in the BIBM proceedings and IEEE Xplore Digital Library. Journal Special Issue Selected high-quality papers will be invited for publication in a special issue in highly respected journal. *Contact* Larbi Boubchir /(//Workshop Chair/),University of Paris 8, France E-mail: larbi.boubchir at univ-paris8.fr -------------- next part -------------- An HTML attachment was scrubbed... URL: From david at irdta.eu Sun Aug 29 04:04:42 2021 From: david at irdta.eu (David Silva - IRDTA) Date: Sun, 29 Aug 2021 10:04:42 +0200 (CEST) Subject: Connectionists: DeepLearn 2022 Winter: early registration September 15 Message-ID: <1364061921.2952992.1630224282299@webmail.strato.com> ****************************************************************** 5th INTERNATIONAL SCHOOL ON DEEP LEARNING DeepLearn 2022 Winter Bournemouth, UK January 17-21, 2022 https://irdta.eu/deeplearn/2022wi/ *********** Co-organized by: Department of Computing and Informatics Bournemouth University Institute for Research Development, Training and Advice ? IRDTA Brussels/London ****************************************************************** Early registration: September 15, 2021 ****************************************************************** SCOPE: DeepLearn 2022 Winter will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw and Las Palmas de Gran Canaria. Deep learning is a branch of artificial intelligence covering a spectrum of current exciting research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of different environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, image analysis, recommender systems, advertising, fraud detection, robotics, games, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience. Most deep learning subareas will be displayed, and main challenges identified through 24 four-hour and a half courses and 3 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main components of the event. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2022 Winter is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2022 Winter will take place in Bournemouth, a coastal resort town on the south coast of England. The venue will be: TBA STRUCTURE: 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. Full in vivo online participation will be possible. However, the organizers want to emphasize the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Yi Ma (University of California, Berkeley), White-box Deep (Convolution) Networks from the Principle of Rate Reduction Daphna Weinshall (Hebrew University of Jerusalem), Curriculum Learning in Deep Networks Eric P. Xing (Carnegie Mellon University), It Is Time for Deep Learning to Understand Its Expense Bills PROFESSORS AND COURSES: Peter L. Bartlett (University of California, Berkeley), [intermediate/advanced] Deep Learning: A Statistical Viewpoint Joachim M. Buhmann (Swiss Federal Institute of Technology, Z?rich), [introductory/advanced] Algorithm Validation for Data Science Nitesh Chawla (University of Notre Dame), [introductory/intermediate] Graph Representation Learning Seungjin Choi (BARO AI Academy), [introductory/intermediate] Bayesian Optimization over Continuous, Discrete, or Hybrid Spaces Sumit Chopra (New York University), [intermediate] Deep Learning in Healthcare R?diger Dillmann (Karlsruhe Institute of Technology), [introductory/intermediate] Building Brains for Robots Marco Duarte (University of Massachusetts, Amherst), [introductory/intermediate] Explainable Machine Learning Charles Elkan (University of California, San Diego), [intermediate] AI and ML Applications in Finance and Retail Rob Fergus (New York University), [intermediate/advanced] Self-supervised Learning of Visual Representations for Recognition and Interaction Jo?o Gama (University of Porto), [introductory] Learning from Data Streams: Challenges, Issues, and Opportunities Claus Horn (Zurich University of Applied Sciences), [intermediate] Deep Learning for Biotechnology Nathalie Japkowicz (American University), [intermediate/advanced] Learning from Class Imbalances Gregor Kasieczka (University of Hamburg), [introductory/intermediate] Deep Learning Fundamental Physics: Rare Signals, Unsupervised Anomaly Detection, and Generative Models Karen Livescu (Toyota Technological Institute at Chicago), [intermediate/advanced] Speech Processing: Automatic Speech Recognition and beyond David McAllester (Toyota Technological Institute at Chicago), [intermediate/advanced] Information Theory for Deep Learning Dhabaleswar K. Panda (Ohio State University), [intermediate] Exploiting High-performance Computing for Deep Learning: Why and How? Tomaso Poggio (Massachusetts Institute of Technology), [advanced] Deep Learning: Theoretical Observations Fabio Roli (University of Cagliari), [introductory/intermediate] Adversarial Machine Learning Jude W. Shavlik (University of Wisconsin, Madison), [introductory/intermediate] Advising, Explaining, Distilling, and Quantizing Deep Neural Networks Kunal Talwar (Apple), [introductory/intermediate] Foundations of Differentially Private Learning Tinne Tuytelaars (KU Leuven), [introductory/intermediate] Continual Learning in Deep Neural Networks Lyle Ungar (University of Pennsylvania), [intermediate] Natural Language Processing using Deep Learning Yu-Dong Zhang (University of Leicester), [introductory/intermediate] Convolutional Neural Networks and Their Applications to COVID-19 Diagnosis OPEN SESSION: An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david at irdta.eu by January 9, 2022. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by January 9, 2022. EMPLOYER SESSION: Firms searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by January 9, 2022. ORGANIZING COMMITTEE: Rashid Bakirov (Bournemouth, co-chair) Nan Jiang (Bournemouth, co-chair) Carlos Mart?n-Vide (Tarragona, program chair) Sara Morales (Brussels) David Silva (London, co-chair) REGISTRATION: It has to be done at https://irdta.eu/deeplearn/2022wi/registration/ The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will get exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. ACCOMMODATION: Accommodation suggestions will be available in due time at https://irdta.eu/deeplearn/2022wi/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. QUESTIONS AND FURTHER INFORMATION: david at irdta.eu ACKNOWLEDGMENTS: Bournemouth University Institute for Research Development, Training and Advice ? IRDTA, Brussels/London -------------- next part -------------- An HTML attachment was scrubbed... URL: From dwang at cse.ohio-state.edu Sun Aug 29 11:21:46 2021 From: dwang at cse.ohio-state.edu (Wang, Deliang) Date: Sun, 29 Aug 2021 15:21:46 +0000 Subject: Connectionists: NEURAL NETWORKS, Sept. 2021 Message-ID: Neural Networks - Volume 141, September 2021 https://www.journals.elsevier.com/neural-networks Noise effect on the temporal patterns of neural synchrony Joel Zirkle, Leonid L. Rubchinsky Real-time face & eye tracking and blink detection using event cameras Cian Ryan, Brian O'Sullivan, Amr Elrasad, Aisling Cahill, ... Etienne Perot Exponential quasi-synchronization of coupled delayed memristive neural networks via intermittent event-triggered control Jiejie Chen, Boshan Chen, Zhigang Zeng Modeling the grid cell activity on non-horizontal surfaces based on oscillatory interference modulated by gravity Yihong Wang, Xuying Xu, Rubin Wang CutCat: An augmentation method for EEG classification Ali Al-Saegh, Shefa A. Dawwd, Jassim M. Abdul-Jabbar Deep ANC: A deep learning approach to active noise control Hao Zhang, DeLiang Wang Automatic, dynamic, and nearly optimal learning rate specification via local quadratic approximation Yingqiu Zhu, Danyang Huang, Yuan Gao, Rui Wu, ... Hansheng Wang Combining a parallel 2D CNN with a self-attention Dilated Residual Network for CTC-based discrete speech emotion recognition Ziping Zhao, Qifei Li, Zixing Zhang, Nicholas Cummins, ... Bjorn W. Schuller Reducing bias to source samples for unsupervised domain adaptation Yalan Ye, Ziwei Huang, Tongjie Pan, Jingjing Li, Heng Tao Shen Deep joint learning for language recognition Lin Li, Zheng Li, Yan Liu, Qingyang Hong Unsupervised foveal vision neural architecture with top-down attention Ryan Burt, Nina N. Thigpen, Andreas Keil, Jose C. Principe Emulation of wildland fire spread simulation using deep learning Frederic Allaire, Vivien Mallet, Jean-Baptiste Filippi Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings Venkata Srikanth Nallanthighal, Zohreh Mostaani, Aki Harma, Helmer Strik, Mathew Magimai-Doss Deep neural network-based generalized sidelobe canceller for dual-channel far-field speech recognition Guanjun Li, Shan Liang, Shuai Nie, Wenju Liu, Zhanlei Yang A neuralized feature engineering method for entity relation extraction Yanping Chen, Weizhe Yang, Kai Wang, Yongbin Qin, ... Qinghua Zheng Radon-Sobolev Variational Auto-Encoders Gabriel Turinici FastTalker: A neural text-to-speech architecture with shallow and group autoregression Rui Liu, Berrak Sisman, Yixing Lin, Haizhou Li Learning emotions latent representation with CVAE for text-driven expressive audiovisual speech synthesis Sara Dahmani, Vincent Colotte, Valerian Girard, Slim Ouni Bifurcations in a fractional-order BAM neural network with four different delays Chengdai Huang, Juan Wang, Xiaoping Chen, Jinde Cao Combination of deep speaker embeddings for diarisation Guangzhi Sun, Chao Zhang, Philip C. Woodland PC-GAIN: Pseudo-label conditional generative adversarial imputation networks for incomplete data Yufeng Wang, Dan Li, Xiang Li, Min Yang QTTNet: Quantized tensor train neural networks for 3D object and video recognition Donghyun Lee, Dingheng Wang, Yukuan Yang, Lei Deng, ... Guoqi Li Synchronization for stochastic coupled networks with Levy noise via event-triggered control Hailing Dong, Ming Luo, Mingqing Xiao Multi-periodicity of switched neural networks with time delays and periodic external inputs under stochastic disturbances Zhenyuan Guo, Jingxuan Ci, Jun Wang Neural network approximation: Three hidden layers are enough Zuowei Shen, Haizhao Yang, Shijun Zhang Pinning bipartite synchronization for coupled reaction-diffusion neural networks with antagonistic interactions and switching topologies Baojun Miao, Xuechen Li, Jungang Lou, Jianquan Lu Saturated impulsive control for synchronization of coupled delayed neural networks Shuchen Wu, Xiaodi Li, Yanhui Ding Learnable Heterogeneous Convolution: Learning both topology and strength H_infinity estimation for stochastic semi-Markovian switching CVNNs with missing measurements and mode-dependent delays Qiang Li, Jinling Liang, Hong Qu Autoencoder networks extract latent variables and encode these variables in their connectomes Matthew Farrell, Stefano Recanatesi, R. Clay Reid, Stefan Mihalas, Eric Shea-Brown A deep network construction that adapts to intrinsic dimensionality beyond the domain Alexander Cloninger, Timo Klock Implicit adversarial data augmentation and robustness with Noise-based Learning Priyadarshini Panda, Kaushik Roy Residual wide-kernel deep convolutional auto-encoder for intelligent rotating machinery fault diagnosis with limited samples Daoguang Yang, Hamid Reza Karimi, Kangkang Sun A dual-stream deep attractor network with multi-domain learning for speech dereverberation and separation Hangting Chen, Pengyuan Zhang Generative Adversarial Network with Multi-branch Discriminator for imbalanced cross-species image-to-image translation Ziqiang Zheng, Zhibin Yu, Yang Wu, Haiyong Zheng, ... Minho Lee CRaDLe: Deep code retrieval based on semantic Dependency Learning Wenchao Gu, Zongjie Li, Cuiyun Gao, Chaozheng Wang, ... Michael R. Lyu -------------- next part -------------- An HTML attachment was scrubbed... URL: From dxkeec at gmail.com Sun Aug 29 12:25:05 2021 From: dxkeec at gmail.com (Dhireesha Kudithipudi) Date: Sun, 29 Aug 2021 11:25:05 -0500 Subject: Connectionists: Open PhD position in Neuromorphic AI Lab Message-ID: Open PhD position in Energy Efficient Machine Learning at the Neuromorphic AI Lab, University of Texas at San Antonio Preferred Start Date: 1/2/2022 (Flexible) Deadline for full consideration: 11/30/2021 We are seeking a Ph.D. student to join an exciting new research project on designing energy-efficient models in continual learning scenarios funded by agencies such as NSF, DARPA and AFRL. Specifically, the candidate is expected to study lightweight deep neural network models, using multi-level model compression and optimization techniques. More often than not, these techniques are neuro-inspired. A successful candidate will interface closely with the hardware team to ensure that the designs are ready to deploy on edge devices. The successful candidate will also be part of a rich and emerging AI community, with the newly established UTSA AI consortium (MATRIX) community. The consortium engages with the private sector, academia, the Greater San Antonio community and international partners to advance the state of the art in human-aware AI. The candidate will be mentored by Dr. Dhireesha Kudithipudi and often in collaboration with leading scientists in the field. Relevant recent publications from the lab are in venues such as CVPR-W, ICML-W, IJCAI-W, DATE, IEEE Signal Processing, IEEE TC. How to Apply: The position will remain open until filled. Applications can be submitted via email to Dr. Kudithipudi (dk at utsa.edu). Applications should be submitted as a single PDF file: 1. Cover letter describing your motivation for applying to this position (1 paragraph) 2. CV and unofficial academic transcripts (with grades if applicable) Qualifications and requirements: 1. Master's degree, or equivalent, in a discipline related to Electrical & Computer Engineering, computer science, computational neuroscience, physics, and related fields. 2. Background and/or strong interest in developing skills in artificial intelligence, computer architecture, machine learning, quantitative methods, and computer arithmetic. 3. Knowledge in programming, preferably in Python. Additional knowledge preferred in deep learning software (Tensorflow/TensorRT, Pytorch, Keras or similar). 4. The successful candidate will be expected to design and perform independent research and publish papers in refereed top conferences and journals, through interdisciplinary research collaborations. 5. Good written and verbal communication skills are essential. 6. A collaborative spirit and the ability to work as part of an interdisciplinary team are essential. -------------- next part -------------- An HTML attachment was scrubbed... URL: From dxkeec at gmail.com Sun Aug 29 12:28:56 2021 From: dxkeec at gmail.com (Dhireesha Kudithipudi) Date: Sun, 29 Aug 2021 11:28:56 -0500 Subject: Connectionists: Open PhD position in Brain-Inspired Artificial Intelligence at the Neuromorphic AI Lab Message-ID: Open PhD position in *Brain-Inspired Artificial Intelligence* at the Neuromorphic AI Lab, University of Texas at San Antonio Preferred Start Date: 01/01/2022 (Flexible) Deadline for full consideration: 11/30/2021 We are seeking a Ph.D. student to join an exciting new research project designing brain-inspired models in continual learning scenarios funded by agencies such as NSF, DARPA and AFRL. Specifically, the candidate is expected to develop and study neural network models using techniques inspired by neuroscience concepts such as consolidation, neurogenesis, metaplasticity, and neuromodulation. The project will involve close interaction with our hardware team to ensure that the designs are ready to deploy on edge devices. The successful candidate will also be part of a rich and emerging AI community within the newly established UTSA AI consortium (MATRIX). The consortium engages with the private sector, academia, the Greater San Antonio community and international partners to advance the state of the art in human-aware AI. The candidate will be mentored by Dr. Dhireesha Kudithipudi and often in collaboration with leading scientists in the field. Relevant recent publications from the lab can be found at CVPR-W, ICML-W, DATE, IEEE Signal Processing Magazine, IEEE TC. How to Apply: The position will remain open until filled. Applications can be submitted via email to Dr. Kudithipudi (dk at utsa.edu). Applications should be submitted as a single PDF file: 1. Cover letter describing your motivation for applying to this position (1 paragraph) 2. CV and unofficial academic transcripts (with grades if applicable) *Qualifications and requirements* 1. Master's degree, or equivalent, in a discipline related to computer science, computational neuroscience, information processing and/or machine learning. 2. Background and/or strong interest in developing skills in artificial intelligence, computer architecture, machine learning, quantitative methods, and computer arithmetic. 3. Knowledge in programming, preferably in Python. Additional knowledge in deep learning software (Tensorflow/TensorRT, Pytorch, Keras or similar) is desirable. 4. The successful candidate will be expected to design and perform independent research and publish papers in refereed top conferences and journals, through interdisciplinary research collaborations. 5. Good written and verbal communication skills are essential. 6. A collaborative spirit and the ability to work as part of an interdisciplinary team are essential. -------------- next part -------------- An HTML attachment was scrubbed... URL: From davrot at neuro.uni-bremen.de Mon Aug 30 07:02:04 2021 From: davrot at neuro.uni-bremen.de (David Rotermund) Date: Mon, 30 Aug 2021 13:02:04 +0200 Subject: Connectionists: Ph.D. student / Postdoc position in machine learning with spiking neurons at University of Bremen, Germany Message-ID: <38953d50-bbf2-b8ef-6a86-94b293212e15@neuro.uni-bremen.de> tl;dr: You looked at our paper Back-Propagation Learning in Deep Spike-By-Spike Networks ( https://www.frontiersin.org/articles/10.3389/fncom.2019.00055/full ) and thought "Interesting idea but I can improve that!" then you may want to tell us your idea... You could end up working on it as a Ph.D. student / Postdoc for the next three years in Bremen, Germany. ------------- The Computational Neuroscience group of Klaus Pawelzik invites applications for an open Ph.D. student / Postdoc position (E13 TV-L 100% for 3 years; all genders welcome) in the project "Efficient Implementation of Spike-by-Spike Neural Networks using Stochastic and Approximative Techniques". We are looking for a person with a strong background in mathematics, programming, and machine learning as well as an intense interest in neuroscience. Someone who is not afraid of cooperating with engineers, since this is a joint project with a focus on hardware development. The overarching goal of our project is to improve the efficiency of spiking artificial neural networks using hardware and algorithmic approximation techniques. Specifically, the project focuses on Spike-by-Spike networks since they offer a balance between computational requirements and biological-realism which keeps the advantages of the biological networks while enabling a compact technical realization. To fully take advantage of the unique features of SbS in terms of robustness and sparseness, dedicated hardware architectures are required. You would join in with numerical simulations, theoretical analyses, as well as through the development of new ideas and approaches for boosting the performance and capabilities of the Spike-By-Spike model. Furthermore, you would also work on combining Spike-By-Spike networks with non spiking deep neuronal networks into hybrid models. The details can be found at http://www.neuro.uni-bremen.de/content/open-position-sbs From miguel-areias at dcc.fc.up.pt Mon Aug 30 14:46:23 2021 From: miguel-areias at dcc.fc.up.pt (Miguel Areias) Date: Mon, 30 Aug 2021 19:46:23 +0100 Subject: Connectionists: Call for Participation - International Conference on Logic Programming (ICLP 2021) Message-ID: <697b7cd3-811f-5309-ad33-768f2d0b18c1@dcc.fc.up.pt> ========================================================================= ???????????????????????????? CALL FOR PARTICIPATION ========================================================================= The 37th International Conference on Logic Programming (ICLP 2021) https://iclp2021.dcc.fc.up.pt/ ========================================================================= The virtual edition of ICLP 2021 will run from September 20 until September 27, 2021. The conference will be held online and we strongly encourage all interested people to register to access the event and interact with other participants. The registration conditions are available at https://iclp2021.dcc.fc.up.pt/index.html#registration The main program is available at https://iclp2021.dcc.fc.up.pt/index-program.html This year's edition includes five outstanding talks by William Cohen (Google AI), John Hooker (CMU), Phokion Kolaitis (UC Santa Cruz and IBM Almaden), Stuart Russell (UC Berkeley) and Jeff Ullman (Stanford University) https://iclp2021.dcc.fc.up.pt/index.html#keynotes and eight affiliated events https://iclp2021.dcc.fc.up.pt/index.html#affiliatedevents Looking forward to meet you in the ICLP 2021 virtual conference. Miguel Areias (on behalf of ICLP 2021 Chairs). ========================================================================= Any additional question can be directed towards ICLP 2021 Chairs: iclp2021 at easychair.org ========================================================================= From paherman at kth.se Mon Aug 30 20:56:27 2021 From: paherman at kth.se (Pawel Herman) Date: Tue, 31 Aug 2021 00:56:27 +0000 Subject: Connectionists: 8th Baltic-Nordic Summer School on Neuroscience and Neuroinformatics (BNNI 2021) Message-ID: <7b8b1ce5b2544887810bef139ec60400@kth.se> Dear Fellow Neuroscientists and Students We would like to invite you to the 8th Baltic-Nordic Summer School on Neuroscience and Neuroinformatics, which will be organised as a virtual event on 21-25 September, 2021. The 8th Baltic-Nordic Summer School on Neuroscience and Neuroinformatics 2021 ?Learning in the Brain and NeuroRobots ? from Molecules to Behaviour? offers interdisciplinary course and covers modelling at different levels of organization of the brain, from single neurons to microcircuits, neural networks and neurorobotics. The course offers lectures on the latest achievements in understanding learning, neural and network dynamics and function in health and disease, neurorobotic theory and applications, and hands-on tutorials on the EBRAINS services and tools. The summer school targets advanced master students, doctoral students and postdoctoral researchers in biomedical and technology sciences, ranging from medicine, biology, psychology, to mathematics, informatics, information technology, physics and chemistry, who would like to get an introduction to neuroinformatics and computational neuroscience and especially the EBRAINS Infrastructure (ebrains.eu). Further information and registration: https://www.humanbrainproject.eu/en/education/BNNI2021/ Best regards Pawel Herman on behalf of the organising committee ------------------------------------ Pawe? Herman Associate Professor, PhD, Docent KTH Royal Institute of Technology School of Electrical Engineering and Computer Science (EECS) Division of Computational Science and Technology (CST) Lindstedtsv?gen 5 114 28 Stockholm, Sweden room 4442 (4th floor, D-building) tel. +46 8 790 6513 -------------- next part -------------- An HTML attachment was scrubbed... URL: From ioannakoroni at csd.auth.gr Tue Aug 31 11:03:42 2021 From: ioannakoroni at csd.auth.gr (Ioanna Koroni) Date: Tue, 31 Aug 2021 18:03:42 +0300 Subject: Connectionists: =?utf-8?q?AI4Media_Workshop_on_=E2=80=9CContent-c?= =?utf-8?b?ZW50ZXJlZCBBSeKAnSwgU2VwdC4gMXN0LCAyMDIxLCAwOTowMC0xODow?= =?utf-8?q?0_CEST?= Message-ID: <046f01d79e79$642114c0$2c633e40$@csd.auth.gr> We are pleased to invite you to the upcoming *AI4Media Workshop on* *"Content-centered AI"* that will take place *on Wednesday, September 1st, 2021* from 09:00 to 18:00 CEST. The goal of this workshop is to present the recent research advances achieved in the AI4Media project on content-centered AI. It collects contributions of AI4Media partners in *fundamental machine learning research* as well as in *innovative AI-based methods and tools for content production and usage*. It will address limitations of Deep Learning related to training with data scarcity, extending the potential applicability of AI to a wider set of media. It will present innovative solutions for (semi-) automated multimedia content production, analysis of content provenance, visual data and audio retrieval, annotation and summarization. The workshop will also host two invited talks by world-renowned scientists: * *Prof. Mohan Kankanhalli*, National University of Singapore, will give a keynote talk on "/Privacy-aware analytics for human attributes from images/, where he will address the key topic of analyzing human emotions, gender and age in images and videos under privacy-preserving conditions. * *Prof. Alan Smeaton*, Dublin City University, will give a keynote on "/Multimedia analysis and multimedia retrieval: Is there a mis-match?/", where he will explore the relationship between visual information and human memory and raise questions on the real effectiveness of the current search and analysis tools that we use. *Learn more and join the workshop **HERE **. * Please feel free to share this invitation among your networks. Kind regards, Filareti Tsalakanidou -- ___________________________________________________ Dr. Filareti Tsalakanidou Electrical and Computer Engineer, Ph.D. Research Associate Information Technologies Institute Centre for Research and Technology Hellas 6th Km Charilaou-Thermi Road 57001, Thermi, Thessaloniki, Greece P.O. Box 60361 Tel.: +30.2311.257706 Fax: +30.2310.474128 Email:filareti at iti.gr -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus From g.goodhill at uq.edu.au Mon Aug 30 15:43:53 2021 From: g.goodhill at uq.edu.au (Geoffrey Goodhill) Date: Mon, 30 Aug 2021 19:43:53 +0000 Subject: Connectionists: Postdoc / Staff Scientist in brain imaging during natural behavior Message-ID: <465A1C09-6ABA-4711-ABE7-11BF7512DD96@uq.edu.au> Postdoc / Staff Scientist in brain imaging during natural behavior The Goodhill lab at Washington University in St Louis is looking for a postdoc or staff scientist for an NIH-funded project to develop novel microscopy methods for whole-brain calcium imaging in freely-behaving zebrafish. This is a collaboration with Oliver Cossairt at Northwestern University. The lab focuses on the formation of neural circuits underlying behavior. This includes developing novel experimental, computational and theoretical methods and applying them to domains including hunting and social behavior, sleep and autism spectrum disorders. In this project we will be constructing new light-field imaging techniques to record the activity of ~100,000 neurons in the zebrafish brain during unconstrained hunting behavior. We are looking for someone with a background in developing new imaging technologies. The lab is fully integrated between experimental and theoretical work. Washington University in St Louis is ranked in the top 10 globally for Neuroscience and Behavior, and offers an outstanding intellectual environment for neuroscience research. The lab is based at the Medical School between the departments of Neuroscience and Developmental Biology, but also has strong links with the Faculty of Engineering. To apply please send a detailed CV and cover letter explaining your interest to g.goodhill at wustl.edu. Professor Geoffrey J Goodhill Departments of Developmental Biology, Neuroscience, Biomedical Engineering, and Electrical and Systems Engineering Washington University School of Medicine St. Louis, MO 63110 https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd Email: g.goodhill at wustl.edu From donatello.conte at univ-tours.fr Tue Aug 31 09:11:41 2021 From: donatello.conte at univ-tours.fr (Donatello Conte) Date: Tue, 31 Aug 2021 15:11:41 +0200 Subject: Connectionists: CfP for Graph Models for Learning and Recognition (GMLR) Track at 37th ACM-SAC 2022 in Brno, Czech Republic Message-ID: <012d01d79e69$bd816ed0$38844c70$@univ-tours.fr> --------------------------------------------------------- Apologies for multiples copies --------------------------------------------------------- Call for Papers Graph Models for Learning and Recognition (GMLR) Track The 37th ACM Symposium on Applied Computing (SAC 2022) April 25-29, 2022, Brno, Czech Republic http://phuselab.di.unimi.it/GMLR2022 Track Chairs Donatello Conte (University of Tours) Giuliano Grossi (University of Milan) Raffaella Lanzarotti (University of Milan) Jianyi Lin (Universit? Cattolica del Sacro Cuore) Jean-Yves Ramel (University of Tours) Scientific Program Committee (in progress) Davide Boscaini (Fondazione Bruno Kessler) Ryan A. Rossi (Adobe Research) ... Important Dates Submission of regular papers: October 15, 2021 Notification of acceptance/rejection: December 10, 2021 Camera-ready copies of accepted papers: December 21, 2021 SAC Conference: April 25 - 29, 2022 Motivations and topics The ACM Symposium on Applied Computing (SAC 2022) has been a primary gathering forum for applied computer scientists, computer engineers, software engineers, and application developers from around the world. SAC 2022 is sponsored by the ACM Special Interest Group on Applied Computing (SIGAPP), and will be held in Brno, Czech Republic. The technical track on Graph Models for Learning and Recognition (GMLR) is the first edition and is organized within SAC 2022. Graphs have gained a lot of attention in the pattern recognition community thanks to their ability to encode both topological and semantic information. Encouraged by the success of CNNs, a wide variety of methods have redefined the notion of convolution for graphs. These new approaches have in general enabled effective training and achieved in many cases better performances than competitors, though at the detriment of computational costs. Typical examples of applications dealing with graph-based representation are: scene graph generation, point clouds classification, and action recognition in computer vision; text classification, inter-relations of documents or words to infer document labels in natural language processing; forecasting traffic speed, volume or the density of roads in traffic networks, whereas in chemistry researchers apply graph-based algorithms to study the graph structure of molecules/compounds. This track intends to focus on all aspects of graph-based representations and models for learning and recognition tasks. GMLR spans, but is not limited to, the following topics: ? Graph Neural Networks: theory and applications ? Deep learning on graphs ? Graph or knowledge representationa learning ? Graphs in pattern recognition ? Graph databases and linked data in AI ? Benchmarks for GNN ? Dynamic, spatial and temporal graphs ? Graph methods in computer vision ? Human behavior and scene understanding ? Social networks analysis ? Data fusion methods in GNN ? Efficient and parallel computation for graph learning algorithms ? Reasoning over knowledge-graphs ? Interactivity, explainability and trust in graph-based learning ? Probabilistic graphical models ? Biomedical data analytics on graphs Authors of selected top papers of this track will be asked to publish an extended version in a Special Issue of a Journal (the journal will be announced soon). Submission Guidelines Authors are invited to submit original and unpublished papers of research and applications for this track. The author(s) name(s) and address(es) must not appear in the body of the paper, and self-reference should be in the third person. This is to facilitate double-blind review. Please, visit the website for more information about submission SAC No-Show Policy Paper registration is required, allowing the inclusion of the paper/poster in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for the paper/poster to be included in the ACM digital library. No-show of registered papers and posters will result in excluding them from the ACM digital library. -------------- next part -------------- An HTML attachment was scrubbed... URL: From kendrick.kay at gmail.com Mon Aug 30 12:50:37 2021 From: kendrick.kay at gmail.com (Kendrick Kay) Date: Mon, 30 Aug 2021 11:50:37 -0500 Subject: Connectionists: CCN 2021 Program Announcement Message-ID: The program for this year's CCN is now available at http://ccneuro.org . Held online from Sep 7-24, 2021, the events include Keynotes & Tutorials: Controversial stimuli: Optimizing experiments to adjudicate among computational hypotheses Nikolaus Kriegeskorte, Tal Golan, Wenxuan Guo Voxelwise Modeling: a powerful framework for recovering functional maps from fMRI data Fatma Deniz, Jack Gallant, Matteo Visconti di Oleggio Castello, Tom Dupre la Tour, Mark Lescroart Flexible identification of population dynamics from neural activity recordings Mikhail Genkin and Tatiana Engel As well as Generative Adversarial Collaborations: What constitutes understanding of ventral pathway function? Charles Connor, Gabriel Kreiman, Carlos R Ponce, Carl Craver, Margaret Livingstone, Martin Schrimpf, Binxu Wang How does visual experience shape representations and transformations along the ventral stream? Maria Bedny, Nancy Kanwisher, Olivier Collignon, Ilker Yildirim, Elizabeth Saccone, Apurva Ratan Murty, Stefania Mattioni How does the brain combine generative models and direct discriminative computations in high-level vision? James J. DiCarlo, Ralf Haefner, Leyla Isik, Talia Konkle, Nikolaus Kriegeskorte, Benjamin Peters, Nicole Rust, Kim Stachenfeld, Joshua B. Tenenbaum, Doris Tsao, Ilker Yildirim What makes representations ?useful?? Ben Baker, Richard Lange, Alessandro Achille, Rosa Cao, Nikolaus Kriegeskorte, Odelia Schwartz, Xaq Pitkow And results from the Algonauts 2021 competition. Please visit http://ccneuro.org for more information. --CCN organizers -------------- next part -------------- An HTML attachment was scrubbed... URL: From Bing.Xue at ecs.vuw.ac.nz Tue Aug 31 17:00:08 2021 From: Bing.Xue at ecs.vuw.ac.nz (Bing XUE) Date: Wed, 1 Sep 2021 09:00:08 +1200 Subject: Connectionists: 3rd CFP EuroGP 2022 - 25th European Conference on Genetic Programming - 20-22 April 2022 Message-ID: Dear Colleague(s), ?*** Apologies for cross-posting *** We would like to invite you to submit papers to EuroGP 2022: THE 25th EUROPEAN CONFERENCE ON GENETIC PROGRAMMING which will be held on April 20-22, 2022 Please visit http://www.evostar.org for more details. *** Important dates *** Submission deadline: 1 November 2021 EvoStar Conference: 20-22 April, 2022 *** EuroGP *** EuroGP is the premier annual conference on Genetic Programming (GP), the oldest and the only meeting worldwide devoted specifically to this branch of evolutionary computation. It is always a high-quality, enjoyable, friendly event, attracting participants from all continents, and offering excellent opportunities for networking, informal contact, and exchange of ideas with fellow researchers. It will feature a mixture of oral presentations and poster sessions and invited keynote speakers. EuroGP is featured in the conference ranking database CORE (http://portal.core.edu.au/conf-ranks/481/) *** EvoStar *** EvoStar is a leading international event devoted to evolutionary computing, comprising four conferences, EuroGP, EvoApplications, EvoCOP, and EvoMUSART. The low-cost registration includes access to all of them, as well as daily lunch and the conference reception and banquet. *** Topics *** Topics to be covered include, but are not limited to: Innovative applications of GP, Theoretical developments, GP performance and behaviour, Fitness landscape analysis of GP, Algorithms, representations and operators for GP, Search-based software engineering, Genetic improvement programming, Evolutionary design, Evolutionary robotics, Tree-based GP and Linear GP, Graph-based GP and Grammar-based GP, Evolvable hardware, Self-reproducing programs, Multi-population GP,? Multi-objective GP, Parallel GP, Probabilistic GP, Object-orientated GP, Hybrid architectures including GP, Coevolution and modularity in GP, Semantics in GP, Unconventional GP, Automatic software maintenance, Evolutionary inductive programming, Evolution of automata or machines. ***the EvoML joint track *** Please visit: http://www.evostar.org/2022/eml/ This joint track on Evolutionary Machine Learning (EML) will provide a specialized forum of discussion and exchange of information for researchers interested in exploring approaches that combine nature and nurture, with the long-term goal of evolving Artificial Intelligence (AI). In response to the growing interest in the area, and consequent advances of the state-of-the-art, the special session covers theoretical and practical advances on the combination of Evolutionary Computation (EC) and Machine Learning (ML) techniques. As a joint EuroGP+EvoAPPS track, authors should decide whether their paper will be treated within EvoApplications or EuroGP at the submission time. *** Paper submission *** High-quality submissions not exceeding 16 pages in Springer LNCS format are now solicited. Accepted papers will be published by Springer-Verlag in the Lecture Notes in Computer Science series. The highest quality papers may also be invited to submit extensions for publication in a special issue of the journal Genetic Programming and Evolvable Machines (GPEM). *** Organization *** Program Chairs: Eric Medvet, University of Trieste, Italy Gisele Pappa, Universidade Federal de Minas Gerais, Brazil Publication Chair: Bing Xue, Victoria University of Wellington *** Program Committee *** (To be announced) For further information please visit http://www.evostar.org. Eric Medvet, Gisele Pappa, and Bing Xue EuroGP Chairs -- ---------------------------------------------- Dr Bing Xue (she/her), MIEEE, MACM Professor | Ahorangi Programme Director of Science | Pouakorangi School of Engineering and Computer Science | Te Kura M?tai P?kaha, P?rorohiko Victoria University of Wellington | Te Herenga Waka New Zealand | Aotearoa Phone: +64 4 463 5542 Homepage: https://homepages.ecs.vuw.ac.nz/~xuebing/index.html ---------------------------------------------- From navlakha at cshl.edu Tue Aug 31 15:15:42 2021 From: navlakha at cshl.edu (Navlakha, Saket) Date: Tue, 31 Aug 2021 19:15:42 +0000 Subject: Connectionists: Post-doc at Cold Spring Harbor Laboratory Message-ID: <4560FECE-772A-4D61-A1CF-407B8FE15454@cshl.edu> We study biological algorithms & data structures used within natural systems, including the brain, plants, the immune system, etc. If you are a PhD computer scientist and interested in working with us, please let me know. Saket Navlakha Associate Professor Cold Spring Harbor Laboratory www.navlakhalab.net