Fwd: [AsilomarSSC] CFP: 2024 Asilomar Conference on Signals, Systems, and Computers

[Artur Dubrawski]

This is a really good venue to consider.

Artur

---------- Forwarded message ---------
From: Linda DeBrunner via AsilomarSSC <asilomarssc at lists.fsu.edu>
Date: Wed, Mar 20, 2024, 4:23 PM
Subject: [AsilomarSSC] CFP: 2024 Asilomar Conference on Signals, Systems,
and Computers
To: Linda DeBrunner via AsilomarSSC <asilomarssc at lists.fsu.edu>


The Asilomar Conference on Signals, Systems, and Computers will be held
Oct. 27-30, 2024. We hope you will consider submitting a paper. *Extended
Summaries are due for consideration by May 1, 2024. *Students that are
first authors are encouraged to participate in the Student Paper Contest,
which requires full paper submissions at this time. Details of the student
paper contest are given on the conference website. Submissions will be
accepted starting April 1, 2024. Notifications of acceptance will be mailed
by mid-July 2024. Full final papers are due shortly after the conference
and published in early 2025. The Call for Papers is attached.

Updates will be posted on the conference website:
https://www.asilomarsscconf.org/.

*Authors are invited to submit papers in the following areas:*
*A. Communication Systems*: 1. Modulation and Coding, 2. Channel Estimation
and Equalization, 3. ML for Communications, 4. Full Duplex, 5. JC&S, 6.
Ultra-Low Latency, 7. Physical Layer Security & Privacy, 8. Underwater
Communications, 9. Wireline & Optical Communications, 10. Satellite
Communications, 11. Communication Schemes for IoT, V2V, etc. 12. 6G and
Beyond
*B. MIMO Communications and Signal Processing: *1. Single- and Multi-User
MIMO, 2. Massive MIMO, 3. MIMO Channel Estimation 4. Cooperation &
Relaying, 5. Interference Management & Awareness, 6. mmWave and THz, 7.
Cell-Free Systems, 8. Reconfigurable Intelligent Surfaces
*C. Networks and Graphs: *1. Network Information Theory, 2. Distributed
Optimization & Algorithms, 3. Graph Signal Processing, 4. Machine Learning
over Graphs, 5. Federated Learning, 6. Wireless Networks, 7. IoT, 8. Social
Networks and Network Science, 9. Data Networks & Computational Offloading,
10. Transportation, UAV & V2V Networks, 11. Power Networks & Smart Grids
*D. Adaptive Systems, Machine Learning, and Data Analytics*: 1. Adaptive
Filtering, 2. Adaptive and Cognitive Systems, 3. Estimation and Inference,
4. Compressive Sensing and Sparse Recovery, 5. Models for High-Dimensional
Large-Scale Data, 6. Optimization, 7. Online Learning and Regret
Minimization, 8. Learning Theory and Algorithms, 9. Self- and
Semi-supervised Learning, 10. Deep Learning, 11. Reinforcement Learning
*E. Array Processing and Multisensor Systems*: 1. Source Localization and
Separation, 2. DoA Estimation, 3. Tensor Models and Processing, 4. ML for
Array Processing and Multisensor Systems, 5. Sparse Sensor Arrays, 6.
Robust Methods, 7. Applications (Imaging, MIMO Radar, JC&S, Sonar,
Microphone Arrays, etc.)
*F. Biomedical Signal and Image Processing*: 1. Molecular and Medical
Imaging, 2. Computational Imaging, 3. Neuroengineering, 4. Processing of
Physiological Signals, 5. Bioinformatics and Computational Biology, 6.
Image Registration and Multimodal Imaging, 7. Functional Imaging, 8. Brain
Machine Interfaces, 9. Neural Signal Processing, 10. Computational
Neuroscience
*G. Architectures and Implementation*: 1. Computer Arithmetic and
Algorithms, 2. Algorithm and Architecture Co-optimization, 3. Hardware
Accelerators, 4. Reconfigurable Processing, 5. Multi- core, Many-core, and
Distributed Systems, 6. Architectures for ML, 7. In-Memory Processing, 8.
Cyber-Physical Systems, 9. Mixed-Signal Processors, 10. Testbeds, 11.
Emerging Technologies
*H. Speech, Image and Video Processing*: 1. Speech Coding, 2. Speech
Recognition, 3. Audio Coding, 4. Document Processing, 5. Models for Speech
& Image Processing, 6. Image & Video Coding, 7. Learning and Autonomous
Systems, 8. Natural Language Processing, 9. Computer Vision, Image and
Video Analysis, 10. Image & Video Forensics, 11. Biometrics & Security, 12.
Hybrid Imaging Systems

Dr. Linda S. DeBrunner
Electrical & Computer Engineering
FAMU-FSU College of Engineering
Florida State University
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