Connectionists: CFP: 4th IEEE Workshop on Pervasive and Resource-constrained Artificial Intelligence (PeRConAI’25)

[Paolo Dini]

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   [Please accept our apologies if you receive multiple copies of this CFP]
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4th IEEE Workshop on Pervasive and Resource-constrained Artificial 
Intelligence (PeRConAI)
co-located with IEEE PerCom 2025, March 17-21, 2025, Washington DC, USA

Website: http://perconai.iit.cnr.it 
<https://urldefense.com/v3/__http://perconai.iit.cnr.it__;!!D9dNQwwGXtA!QWOqdtRbbS04WTruHR9bBpceE5iCrIJmUEw3q_PXt2ohUb521g4z1EZw4o82NqTzwG9lvtNpDE7ug8Q_2JTauSRHZQ5znRhWG0qnhw$>
Email contact for info: perconai at iit.cnr.it 
<https://urldefense.com/v3/__https://mailto:perconai@iit.cnr.it__;!!D9dNQwwGXtA!QWOqdtRbbS04WTruHR9bBpceE5iCrIJmUEw3q_PXt2ohUb521g4z1EZw4o82NqTzwG9lvtNpDE7ug8Q_2JTauSRHZQ5znRhL-tLekw$>

This year’s PeRConAI enjoys the joint technical co-sponsorship of the 
SONATA (https://sonata.cttc.es) project.

Important dates
---------------
* Paper submission deadline: November 17th, 2024
* Paper notification: January 8th, 2025

Call for Papers
---------------
PeRConAI will focus on solutions that contribute to advancing truly 
pervasive and liquid AI, enabling edge devices, regardless of their 
available resources, to accomplish training and inference under full, 
weak, or no supervision.

The increasing pervasiveness of edge devices and the high availability, 
velocity, and volatility of data generated and collected at the edge of 
the internet are pushing towards a paradigm shift in the design of 
AI-based systems. AI systems are moving the execution of both training 
and inference tasks from powerful and remote data centers where all data 
is available in a centralized fashion to more pervasive and 
distributed/decentralized systems at the edge of the internet, working 
in proximity to where data is physically generated and/or collected.
The design of edge AI systems must leverage the collaboration of several 
heterogeneous devices working in a highly dynamic context both in terms 
of processing capabilities and connectivity. Beyond resource 
limitations, data locally collected or generated by devices might 
statistically differ from one device to another, even if collected by 
the same application or belonging to the same phenomenon. Finally, human 
intervention in the AI process is still predominant, especially in its 
initial phases, e.g., data preparation, labeling, and pre-processing, 
thus limiting the necessary speed up to make AI truly pervasive.

Topics of interest
------------------
The PeRConAI workshop aims to foster the development and circulation of 
new ideas and research directions on pervasive and resource-constrained 
AI/ML, bringing together practitioners and researchers working on the 
intersection between pervasive computing and machine learning.
The PeRConAI workshop solicits contributions on, but not limited to, the 
following topics:

** Foundations of Advanced Machine learning algorithms and methods for 
pervasive systems subject to resource limitations addressing the 
following open challenges:

- Distributed/decentralized Machine Learning for resource-constrained 
devices (e.g., resource-efficient federated learning);
- Lightweight ML models for on-device training/inference in pervasive 
computing (e.g., GRU, ELM, MHN, etc.);
- Sustainable AI through new, brain- and bio-inspired ML algorithms 
exploiting energy-efficient hardware, e.g., FPGA, Neuromorphic HW;
- Compression of deep learning models for real-time inference
- Privacy-preserving distributed/decentralized learning in pervasive and 
resource-constrained scenarios;
- Trustworthiness of distributed/decentralized learning systems in 
pervasive and resource-constrained scenarios;
- Semi-supervised and self-supervised learning systems in pervasive and 
resource-constrained scenarios;
- Learning with imbalanced data in pervasive and resource-constrained 
scenarios;
- Continual learning in pervasive and resource-constrained scenarios;
Over-the-air computing for distributed/decentralized learning systems in 
pervasive and resource-constrained scenarios.

** Applications of Advanced Machine learning algorithms, methods, and 
approaches for pervasive computing under resource limitations applied to 
the following application domains:

- Health and well-being applications (e.g., activity recognition, health 
monitoring).
- Anomaly/Novelty detection (e.g., Industry 4.0, intrusion detection, 
privacy, and security).
- Audio signal processing (e.g., sound event detection, speech 
recognition/processing).
- Video stream processing on resource-constrained devices.
- Natural Language Processing and Information Retrieval (e.g., 
conversational applications running on resource-constrained, mobile, or
edge devices).
- Intersection between mobile computing with ML/DL on 
resource-constrained devices.
- Any other real-world applications and case studies where the 
pervasiveness of resource-constrained devices is central for knowledge 
extraction.

Submissions Guidelines
----------------------
All papers must be at most 6 pages of technical content, typeset in 
double-column IEEE format using 10pt fonts on US letter paper, with all 
fonts embedded. In PeRConAI, the peer-review process will be single-blind.
Submissions must be made via EasyChair. The IEEE LaTeX and Microsoft 
Word templates and related information can be found on the IEEE Computer 
Society website.

PeRConAI will be held in conjunction with IEEE PerCom 2025 
(https://www.percom.org 
<https://urldefense.com/v3/__https://www.percom.org__;!!D9dNQwwGXtA!QWOqdtRbbS04WTruHR9bBpceE5iCrIJmUEw3q_PXt2ohUb521g4z1EZw4o82NqTzwG9lvtNpDE7ug8Q_2JTauSRHZQ5znRi3ZhRAbw$>). 
All accepted papers will be included in the Percom workshop proceedings 
and indexed in the IEEEXplore digital library. At least one author must 
register for the conference in full and present the paper during the 
workshop.

Steps:
1- Follow the submission link: 
https://easychair.org/my/conference?conf=percom2025 
<https://urldefense.com/v3/__https://easychair.org/my/conference?conf=percom2025__;!!D9dNQwwGXtA!QWOqdtRbbS04WTruHR9bBpceE5iCrIJmUEw3q_PXt2ohUb521g4z1EZw4o82NqTzwG9lvtNpDE7ug8Q_2JTauSRHZQ5znRirKlVB7g$>
2- Select PeRConAI (4th Workshop on Pervasive and Resource-Constrained AI)
3- Fill in the form and upload the paper in PDF format.


Organizing Committee
--------------------
Prof. Plamen Angelov, Lancaster University, UK
Prof. Mario Luca Bernardi, University of Sannio, IT
Dr. Paolo Dini, CTTC, ES
Dr. Franco Maria Nardini, ISTI-CNR, IT
Prof. Riccardo Pecori, eCampus University, IT and IMEM-CNR, IT
Dr. Lorenzo Valerio, IIT-CNR, IT

-- 

*Paolo Dini*
Researcher (R4)
** Sustainable Artificial Intelligence (SAI) research unit
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Av. Carl Friedrich Gauss, 7 - Building B4
08860 - Castelldefels
Tel.: +34 93 645 29 00

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