From Mobile Internet to Mobile Intelligence: New Challenges and Opportunities of Future Wireless Networks

10:30am - 11:30am
Zoom seminar: Meeting ID: 993 6888 4175 Passcode: 652552


The continual evolution of wireless communications technologies has profoundly changed our daily lives. Mobile Internet represents a recent revolution that has been enabled by the seamless mobile broadband access of 4G LTE networks. It in turn has empowered various groundbreaking mobile applications, such as online-to-offline commerce, mobile payment, mobile social networks, and so on. Meanwhile, with the recent revival of artificial intelligence (AI), a plethora of intelligent mobile applications emerge, e.g., augmented/virtual reality, mobile robots, autonomous driving, etc. Given the limited onboard computing resource, power supply, and sensing capability of mobile devices, these applications will critically rely on effective communications to access external computing resources (e.g., cloud and edge servers) and exchange data (e.g., sensing data, intermediate features, or AI models) for better user experience, perception capability, robustness and safety. This calls for a paradigm shift in wireless networking, from “data-oriented communications”, which maximize data rates, to “task-oriented communications”, where the data transmission is an intermediate step and is to be optimized for the downstream task. This talk will introduce new research problems of task-oriented communications for mobile intelligence, which demand integrated designs of communication strategies and machine learning models. It will present a pragmatic end-to-end design approach based on an information bottleneck principle and neural architecture design. Moreover, it will also introduce promising tools for further theoretical and algorithmic investigations, which are recently developed in structured high-dimensional estimation and deep learning.

Event Format
Speakers / Performers:
Professor Jun Zhang
Assistant Professor, Department of Electronic and Information Engineering (EIE), The Hong Kong Polytechnic University (PolyU)

Jun Zhang received the B.Eng. degree in Electronic Engineering from the University of Science and Technology of China in 2004, the M.Phil. degree in Information Engineering from the Chinese University of Hong Kong in 2006, and the Ph.D. degree in Electrical and Computer Engineering from the University of Texas at Austin in 2009. He is an Assistant Professor in the Department of Electronic and Information Engineering at the Hong Kong Polytechnic University. Previously he was a Research Assistant Professor with the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology. His research interests include wireless communications and networking, mobile edge computing and edge AI, distributed learning and optimization, and big data analytics.

Dr. Zhang co-authored the book Fundamentals of LTE (Prentice-Hall, 2010). He is a co-recipient of several best paper awards, including the 2021 Best Survey Paper Award of the IEEE Communications Society, the 2019 IEEE Communications Society & Information Theory Society Joint Paper Award, and the 2016 Marconi Prize Paper Award in Wireless Communications. Two papers he co-authored received the Young Author Best Paper Award of the IEEE Signal Processing Society in 2016 and 2018, respectively. He also received the 2016 IEEE ComSoc Asia-Pacific Best Young Researcher Award. He is an Editor of IEEE Transactions on Communications, and was an editor of IEEE Transactions on Wireless Communications (2015-2020). He served as a MAC track co-chair for IEEE Wireless Communications and Networking Conference (WCNC) 2011 and a co-chair for the Wireless Communications Symposium of IEEE International Conference on Communications (ICC) 2021.

Department of Electronic & Computer Engineering
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