Special Session I: Machine Learning Methods for Intelligent Perception and Advanced Signal Processing


Machine learning has emerged as a transformative paradigm in modern signal processing, offering powerful tools for extracting knowledge and enabling intelligent perception from complex and high-dimensional data. Unlike traditional approaches that rely heavily on model assumptions, learning-based methods can adaptively capture nonlinear structures, discover latent representations, and enhance robustness in dynamic and uncertain environments. These capabilities are crucial for advancing next-generation sensing and perception systems, where radar, wireless communication, sonar, biomedical, audio, and multimodal signals must be processed efficiently and intelligently.

This special session aims to highlight recent progress and emerging directions in the integration of machine learning with advanced signal processing. We encourage contributions that present novel methods, theoretical foundations, and innovative applications, with a particular focus on machine learning-driven perception and advanced signal processing technologies. Topics of interest include, but are not limited to:

• Machine learning algorithms for radar, wireless communication, sonar, and array signal processing
• Robust learning methods for complex and dynamic environments
• Data-driven approaches for intelligent sensing and multidimensional signal processing
• Efficient learning in finite-dimensional and structured feature spaces
• Deep and reinforcement learning for perceptual intelligence and decision-making
• Distributed learning systems for advanced signal processing
• Autonomous systems and environmental sensing enabled by learning-based methods
• Anomaly detection, predictive maintenance, and reliability in perceptual data analysis
• Learning-driven biometric, speech, and multimodal perception
• Applications in robotics, smart manufacturing, remote sensing, and healthcare

We invite researchers and practitioners from academia and industry to contribute original works that explore the synergy between machine learning and advanced signal processing for intelligent perception.

Submission Method


Electronic Submission System (.pdf) (Please select and click Special Session 1: Machine Learning Methods for Intelligent Perception and Advanced Signal Processing to submit.)

Organizer


Shiyuan Wang (Senior Member, IEEE) received the Ph.D. degree in circuit and system from Chongqing University, Chongqing, in 2011. He was a Research Associate at The Hong Kong Polytechnic University in 2013 and a Research Fellow at The City University of Hong Kong in 2023, respectively. He has published one monograph and more than 150 papers in various journals and conference proceedings. From 2018 to 2021, he served as an Associate Editor for IEEE TCAS II, a leading journal in circuits and systems. Currently, he is a Professor with the College of Electronic and Information Engineering, Southwest University, Chongqing, and continues to serve as an Associate Editor for Symmetry. His research interests include machine learning, adaptive signal processing, nonlinear dynamics, simultaneous localization, and mapping (SLAM).



Yunfei Zheng received the Ph.D. degree in control science and engineering from Xi’an Jiaotong University, Xi’an, China, in 2021. He was a Postdoctoral Researcher with the Southwest University, Chongqing, China, from 2021 to 2024. He has published more than 30 papers. Currently, he is a Lecturer with the College of Electronic and Information Engineering, Southwest University, Chongqing. His current research interests include machine learning and adaptive signal processing.

 

 

Kui Xiong (Member, IEEE) received the B.S. degree in electronic information science and technology from Zhejiang Sci-Tech University, Hangzhou, China, in 2017, the M.S. degree in signal and information processing from Southwest University, Chongqing, China, in 2020, and the Ph.D. degree in information and communication engineering from University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2024. He is currently a Postdoctoral Fellow with the School of Information and Communication Engineering, UESTC, Chengdu, China. His current research interests include multiradar cooperative perception, multiagent system, and adaptive signal processing.