Machine Learning, Deep Learning and Computational intelligence for CSI Compression and Semantic Communication
Goal: The objective of the workshop to explore the usage of existing well established Machine Learning/ Deep learning and Computational intelligence algorithms for CSI Compression and semantic communication. The workshop acts as the platform for research scholars from Machine learning area and Communication area to work together to achieve the promising solutions to Semantic Communication.
Topics include the following (Not limited to):
- Dimensionality reduction techniques for Semantic Communication for classification that include
PCA, LDA, KLDA, ICA etc . - Semantic communication using Large Language Model
- Robust precoder design for Semantic Communication with various channel model
- Semantic communication for regression
- Multi-source Semantic Communication
- Multi-task Semantic communication
- MIMO-OFDM based semantic communication
- OTFS based semantic communication
- NOMA based semantic communication
- IRS based semantic communication
- CSI Compression and Estimation
- Number of expected submissions: 25
- Number of expected participants: 6 to 8 papers
Tentative list of Technical Program Committee
- Arumugam Nallanathan, Professor of wireless communication, Queen Mary , University of
London - Dushantha Nalin K. Jayakody , Professor, Lusofona University, Portugal
- Dr.P.Maheswarn, Assistant professor, NIT,Tiruchirappalli
- Dr.P.Sudharsan, Assistant professor, NIT, Tiruchirappalli
- Dr.Prabhat Kumar, Assistant professor, VNIT,Nagpur
- Dr.Sovanjyoti Giri, Assistant professor, NIT,Tiruchirappalli
- Dr. Anamika Singh, VNIT, Nagpur
and other Faculty with relevant field from the following Institute of National importance (Government of
India):
- Indian Institute of Technology (IITs)
- National Institute of Technology (NITs)
- Indian Institute on Science Education and Research (IISER’s).
Workshop Organizer
E.S.Gopi
(National Insitute of Technology, Tiruchirappalli, India)
Bio: Dr. E. S. Gopi is a professor in the Department of Electronics and Communication Engineering at the National Institute of Technology, Tiruchirappalli (Government of India), with 25+ years of experience in teaching and research. He is currently an IEEE senior member of the Computational Intelligence Society and the Signal Processing Society.
He has authored eight books and edited three publications with Springer, primarily focusing on signal processing and pattern recognition. His book Pattern Recognition and Computational Intelligence using MATLAB was recognized by Book Authority as a notable resource in the field. In addition, he serves as the series editor for Springer’s Signals and Communication Technology series. He has contributed to several research publications, including journal articles, book chapters, and conference proceedings. His publications include articles in IEEE Transactions on Cognitive Communications and Networking, IEEE Networking Letters, IEEE Geoscience and Remote Sensing Letters, IEEE Transactions on Emerging Topics in Computational Intelligence and the Q1 journals published by , Elsevier namely Neurocomputing, Applied Mathematics and Computation, Expert Systems with Applications, Machine Learning with Applications, Ecological Informatics, Computers & Electrical Engineering and Swarm and Evolutionary Computation. He has also organized several academic events, including the virtual international conferences MDCWC2020 and MDCWC2023, with proceedings published by Springer. He actively engages with the IEEE community as the Workshop, Tutorials & Symposia Officer for the Machine Learning for Communications Emerging Technologies Initiative.
He has been invited to speak at platforms like the Global Initiative of Academic Networks (GIAN) and the IEEE Training School on Machine Learning for Wireless Communication. His research interests include machine intelligence, pattern recognition, statistical signal processing, and computational intelligence.
Recent relevant publications by the Pattern recognition and Computational intelligence Group (Headed by the Organizer)
- [1] S. M. Baby and E. S. Gopi, “Complex Valued Linear Discriminant Analysis on mmWave Radar Face Signatures for Task-Oriented Semantic Communication,” in IEEE Transactions on Cognitive Communications and Networking, doi: 10.1109/TCCN.2025.3598379,2025
- [2] K. C. and E. S. Gopi, “CSI Compression With Kernel-Based Sparsity Learning for FDD Massive MIMO Systems,” in IEEE Transactions on Cognitive Communications and Networking, vol. 11, no. 4, pp. 2149-2160, Aug. 2025, doi: 10.1109/TCCN.2024.3516039.
- [3]Simy M. Baby, E.S. Gopi, Complex chromatic imaging for enhanced radar face recognition Elsevier journal on Computers and Electrical Engineering, Volume 123, Part C, 2025, 110198, ISSN 0045-7906
- [4] C. Kiruthika and E. S. Gopi, “FBCNet: Fusion Basis Complex-Valued Neural Network for CSI Compression in Massive MIMO Networks,” in IEEE Networking Letters, vol. 6, no. 4, pp. 262-266, Dec. 2024,