[Keynote I]: 11:20 ~ 11:50, February 25, 2026 (Wednesday)
Prof. Ning Zhang (University of Windsor, Canada)
Task Offloading in Mobile Edge Computing for Internet of Things
Abstract:
Internet of things (IoT) lays the foundation for various emerging applications. As IoT devices are generally constrained with resources, mobile edge computing is proposed whereby data generated by IoT devices can be offloaded to nearby edge servers, so that their tasks can be served locally in real-time. Due to the dynamic, heterogenous, and time-varying operating environment, it is very challenging to utilize heterogeneous resources in an efficient way to meet the service requirements. In this talk, two research works on offloading will be presented, including i) deep reinforcement learning aided dynamic task offloading for IoT; and ii) multi-agent deep reinforcement learning for offloading in vehicular edge computing. Finally, future research directions are discussed.
Biography
Dr. Ning Zhang is a Full Professor and Canada Research Chair in the Department of Electrical and Computer Engineering at University of Windsor. He received the Ph.D degree in Electrical and Computer Engineering from University of Waterloo, Canada, in Jan. 2015. After that, he was a postdoc research fellow at University of Waterloo and University of Toronto, respectively. His research interests include connected vehicles, mobile edge computing, wireless networking, and security. He is a member of Royal Society of Canada College, a Distinguished Lecturer of IEEE, and a Highly Cited Researcher (Web of Science). He serves as the Chair for IEEE Technical Committee on Cognitive Networks and the Vice Chair for IEEE Technical Committee on Big Data. He also serves/served as an Associate Editor of IEEE Transactions on Mobile Computing, IEEE Communications Surveys and Tutorials, IEEE Internet of Things Journal, and IEEE Transactions on Cognitive Communications and Networking.
[Keynote II]: 11:50 ~ 12:20, February 25, 2026 (Wednesday)
Dr. Sei Naito (KDDI Research, Japan)
Evolution of Processing and Transmission Technology toward Physical AI and 6G
Abstract:
As we approach 2030, discussions surrounding 6G wireless technology are gaining momentum, with global research and development advancing at an unprecedented pace toward Physical AI as a key target application. This keynote will provide a comprehensive overview of 6G wireless and Physical AI, followed by an in-depth examination of the latest trends in processing and transmission technologies that enable these innovations. The presentation will highlight initiatives within the KDDI Group, showcasing efforts to drive technological progress in this rapidly evolving domain.
Biography
Sei Naito received his B.E., M.E., and Ph.D. degrees from Waseda University in 1994, 1996, and 2006, respectively. He joined Kokusai Densin Denwa Corporation (now KDDI Corporation) in 1996. Throughout his career, he has contributed to the advancement of television-related technologies and services through innovative and practical research and development, with a primary focus on compression coding and video signal processing. He is currently Executive Vice President of KDDI Research Inc., Japan.