Track 2

Track 2. AI-Driven Communications & Semantic Networking

Chair: Kai Niu, Beijing University of Posts and Telecommunications, China
Co-Chair: Jincheng Dai, Beijing University of Posts and Telecommunications, China
Co-Chair: Shuo Shao, University of Shanghai for Science and Technology, China

This track focuses on the integration of artificial intelligence with communication systems and semantic networking. It explores how AI-enabled perception, semantic understanding, and intelligent decision-making can transform traditional communication architectures. By leveraging semantic encoding, knowledge-aware transmission, and adaptive network control, AI-driven communications aim to significantly improve spectral efficiency, reliability, and energy efficiency. Semantic networking further enables meaning-oriented information exchange, reducing redundant data transmission while enhancing service quality. This track welcomes contributions on theoretical foundations, system design, and practical applications, supporting intelligent connectivity for next-generation networks and emerging intelligent services.

 Submission Link: https://easychair.org/conferences/?conf=icccas2026
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Track Chair Introduction

 

Kai Niu, Beijing University of Posts and Telecommunications, China

 

Biography: Niu Kai received the B.S. degree in information engineering and the Ph.D. degree in signal and information processing from Beijing University of Posts and Telecommunications (BUPT), Beijing, China, in 1998 and 2003, respectively. He is currently a Professor with the School of Artificial Intelligence, BUPT. His research interests include channel coding theory and applications, semantic communication and broadband wireless communication. He has published more than 200 academic papers, and his proposed high performance compilation code algorithm for polar code has become the mainstream scheme of 5G standard, and won the first prize of Natural Science of Science and Technology Award of the Chinese Institute of Electronics.

 

Jincheng Dai, Beijing University of Posts and Telecommunications, China

 

Biography: Jincheng Dai (Member, IEEE) received the B.S. and Ph.D. degrees from the Beijing University of Posts and Telecommunications (BUPT), Beijing, China. He is currently an Associate Professor with the School of Artificial Intelligence and the Key Laboratory of Universal Wireless Communications, Ministry of Education, BUPT. His research interests include AI for coding and communications. He has been selected for the Beijing Nova Program, the China Association for Science and Technology’s (CAST) Young Elite Scientists Sponsorship Program, and the Xiaomi Young Scholars Program. As a core contributor, he has received the First-Class Natural Science Award of the Chinese Institute of Electronics. He has received several accolades, such as the Excellent Science and Technology Paper Award from CAST.

 

Shuo Shao, University of Shanghai for Science and Technology, China

 

Biography: Shuo Shao received the B.A. degree from Southeast University, China, in 2011; the M.A.Sc degree from McMaster University, Canada, in 2013; and the Ph.D. degree from Texas A&M University, U.S., in 2017. He joined Shanghai Jiao Tong University, China, in 2017 as an Assistant Professor and was promoted to Associate Professor in 2021. He is currently with University of Shanghai for Science and Technology as an Associate Professor. He is a recipient of the Shanghai Young Talent Sailing Project and the best paper award of IEEE WCSP 2022 and IEEE/CIC ICCC 2025. His research interests include network information theory and intelligent communications.