Keynote Speakers_2025
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Fellow of IEEE Speech Title: Connecting Small Devices for Big AI Kaibin Huang received the B.Eng. and M.Eng. degrees from the National University of Singapore and the Ph.D. degree from The University of Texas at Austin, all in electrical engineering. He is a Professor and the Head at the Dept. of Electrical and Electronic Engineering, The University of Hong Kong (HKU), Hong Kong. He received the IEEE Communication Society’s 2021 Best Survey Paper, 2019 Best Tutorial Paper, 2019 and 2023 Asia–Pacific Outstanding Paper, 2015 Asia–Pacific Best Paper Award, and the best paper awards at IEEE GLOBECOM 2006 and IEEE/CIC ICCC 2018. He has been named as a Highly Cited Researcher by Clarivate in 2019-2023 and an AI 2000 Most Influential Scholar (Top 30 in Internet of Things) in 2023-2024. He is a Fellow of IEEE and was an IEEE Distinguished Lecturer of both the IEEE Communications Society and the IEEE Vehicular Technology Society. He is a member of the Engineering Panel of Hong Kong Research Grants Council (RGC) and a RGC Research Fellow (2021 Class). He received the Outstanding Teaching Award from Yonsei University, South Korea, in 2011. He is an Area Editor of IEEE Transactions on Wireless Communications, IEEE Transactions on Machine Learning in Communications and Networking, and IEEE Transactions on Green Communications and Networking. Previously, he served on the Editorial Boards for IEEE Journal on Selected Areas in Communications (JSAC) and IEEE Wireless Communication Letters. He has guest edited special issues of IEEE JSAC, IEEE Journal of Selected Areas in Signal Processing, and IEEE Communications Magazine, and IEEE Network. He served as the Lead Chair for the Wireless Communications Symposium of IEEE Globecom 2017 and the Communication Theory Symposium of IEEE GLOBECOM 2023 and 2014, and the TPC Co-chair for IEEE PIMRC 2017 and IEEE CTW 2023 and 2013. He is the founding President of the HKU chapter of National Academy of Inventors. |
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Fellow of IEEE
Dr. Rui Zhang received the B.Eng. (first-class Hons.) and M.Eng. degrees from National University of Singapore and the Ph.D. degree from Stanford University, all in electrical engineering. He is now a Principal’s Diligence Chair Professor in School of Science and Engineering and Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong, Shenzhen. He is also a Professor with the Department of Electrical and Computer Engineering, National University of Singapore. His current research interests include wireless power transfer, UAV/satellite communications, intelligent reflecting surface (IRS) and reconfigurable MIMO systems. He has published over 500 papers, which have been cited more than 100,000 times with the h-index over 130 (Google Scholar). He has been listed as a Highly Cited Researcher by Thomson Reuters / Clarivate Analytics since 2015. He was the recipient of the IEEE Communications Society Asia-Pacific Region Best Young Researcher Award in 2011, the Young Researcher Award of National University of Singapore in 2015, the Recognition Award of WTC, SPCC and TCCN Technical Committees of the IEEE Communications Society in 2020, 2021 and 2023, respectively. He received 18 IEEE Best Journal Paper Awards, including the IEEE Marconi Prize Paper Award in Wireless Communications (twice), the IEEE Communications Society Heinrich Hertz Prize Paper Award (thrice), the IEEE Communications Society Stephen O. Rice Prize, the IEEE Signal Processing Society Best Paper Award, etc. He has served as an Editor for several IEEE journals, including TWC, TCOM, JSAC, TSP, etc., and as TPC co-chair or organizing committee member for over 30 international conferences. He served as an IEEE Distinguished Lecturer of IEEE Communications Society and IEEE Signal Processing Society. He is a Fellow of IEEE and the Academy of Engineering Singapore. |
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Fellow of IEEE Yong Zeng, IEEE Fellow, young chief professor of Southeast University and Purple Mountain Laboratory, national youth high-level talent, Jiangsu province distinguished young researcher, Clarivate Analytics Highly Cited Researcher for 6 consecutive years (2019-2024), AI2000 Most Influential Scholars in the field of Internet of Things for 4 consecutive years (2021-2024), Stanford "Top 2% of Scientists in the World - Lifetime Influence". Prof. Zeng is the recipient of Australia Research Council (ARC) Discovery Early Career Researcher Award (DECRA), IEEE Communications Society Asia-Pacific Outstanding Young Researcher Award, and won 8 international and domestic best paper awards including IEEE Marconi Award (2020 and 2024), Heinrich Hertz Award (2017 and 2020), etc. Prof. Zeng proposed the concept of channel knowledge map (CKM), and his works have been cited by more than 29,000 times. He serves on the editorial board of SCI journals such as IEEE Transactions on Communications, IEEE Transactions on Mobile Computing, and IEEE Communications Letters, and leading guest editor of journals including IEEE ComMag, Wireless ComMag, China Communications, and Science China Information Sciences. Prof. Zeng was elevated to IEEE Fellow“for contributions to unmanned aerial vehicle communications and wireless power transfer”. Speech Title: Generative AI based Channel Knowledge Map Construction and Utilization Abstract: Existing wireless communication and sensing systems are mainly based on the traditional “environment-unaware” paradigm, which fails to fully exploit the prior information of the local wireless environment, resulting in inefficient environment sensing and channel acquisition. This makes it difficult to meet the future needs with the developing trends such as larger channel dimensions, higher node densities, and more cost-effective hardware. On the other hand, the recently proposed concept of channel knowledge map (CKM) aims to build channel knowledge foundations that learn the intrinsic characteristics of the local wireless environment by fusing massive historical data of all terminals in the area, thereby enables the direct acquisition of environmental priors in advance based on (virtual) terminal location information. This enables the paradigm shift from the traditional environment-unaware to the future environment-aware communication and sensing, offering new ideas for efficient environment sensing and channel acquisition. This talk will introduce the latest research progress in the construction and application of CKM. By discussing the basic principles of CKM, typical cases of communication and sensing based on CKM, the theories and methods of CKM construction based on generative AI, as well as preliminary experimental verification, we will try to answer the five fundamental questions about CKM (2W+3H): What is CKM, why needs CKM, how to build and utilize CKM, and how to build prototypes? |
