Keynote Speakers

Prof. Xianbin Wang
Western University, Canada

Speech Title: Beyond ISAC: Unifying Heterogeneous Service Provisioning in 6G

Abstract: The unprecedented deployment of wireless infrastructures and their rapid convergence with computing and vertical applications have fundamentally transformed our lifestyles and industries. Future wireless networks, particularly 6G, are expected to support a diverse range of applications by integrating heterogeneous services. These networks will not only enhance traditional connectivity-centric functions but also introduce emerging beyond-communication capabilities. Despite recent advancements in integrated sensing and communications (ISAC), current designs remain static, isolated, and functionally limited, creating significant challenges in meeting the diverse requirements of future applications while operating under stringent resource constraints. This presentation will start with an in-depth overview of these technical challenges in integrative 6G service provisioning. New 6G design strategies and operational objectives for concurrent heterogeneous service provisioning will be discussed. Furthermore, a new multi-dimensional multiple access (MDMA) technique as an inclusive enabling platform to intelligently integrate various capabilities by shared access to multi-dimensional radio resources will be presented.

Biodata: Dr. Xianbin Wang is a Distinguished University Professor and a Tier-1 Canada Research Chair in Trusted Communications and Computing at Western University, Canada. His current research interests include 5G/6G technologies, Internet of Things, machine learning, communications security, and intelligent communications. He has over 600 highly cited journals and conference papers, in addition to over 30 granted and pending patents and several standard contributions.
Dr. Wang is a Fellow of IEEE, a Fellow of the Canadian Academy of Engineering and a Fellow of the Engineering Institute of Canada. He has received many prestigious awards and recognitions, including the IEEE Canada R. A. Fessenden Award, Canada Research Chair, Engineering Research Excellence Award at Western University, Canadian Federal Government Public Service Award, Ontario Early Researcher Award, and 10 Best Paper Awards. He is currently a member of the Senate, Senate Committee on Academic Policy and Senate Committee on University Planning at Western. He has been involved in many flagship conferences, including GLOBECOM, ICC, VTC, PIMRC, WCNC, CCECE, and ICNC, in different roles, such as General Chair, TPC Chair, Symposium Chair, Tutorial Instructor, Track Chair, Session Chair, and Keynote Speaker. He serves/has served as the Editor-in-Chief, Associate Editor-in-Chief, and editor/associate editor for over ten journals. He has served on the IEEE Fellow Committee and the Fellow Committee of IEEE Communications Society. He was the Chair of the IEEE ComSoc Signal Processing and Computing for Communications (SPCC) Technical Committee and is currently serving as the Central Area Chair of IEEE Canada.

Prof. Zuqing Zhu
University of Science and Technology of China, China

Speech Title: Accelerating Collective Communications with Mutual Benefits of Optical Rackless DC and In-Network Computing

Abstract: We propose a novel data center (DC) architecture to explore the mutual benefits of optical rackless data center (ORDC) and in-network computing for accelerating collective communications for emerging applications such as MapReduce clasters and Large Language Model training. Our experimental results indicate that the proposal reduces job completion time of collective communications by 27:4% to 43.3% over traditional benchmarks.

Biodata: Dr. Zuqing Zhu received his Ph.D. degree from the Department of Electrical and Computer Engineering, University of California, Davis, in 2007. From 2007 to 2011, he worked in the Service Provider Technology Group of Cisco Systems, San Jose, California, as a Senior Engineer. In January 2011, he joined the University of Science and Technology of China, where he currently is a Full Professor in the School of Information Science and Technology. He has published 390+ papers in peer-reviewed journals and conferences. He is the Steering Committee Chair of the IEEE International Conference on High Performance Switching and Routing (HPSR), and was the Chair of the Technical Committee on Optical Networking (ONTC) in IEEE Communications Society. He is a Fellow of IEEE.

Invite Speakers

Dr. Ying Cui
Hong Kong University of Science and Technology (Guangzhou), China

Speech Title: AI-Assisted Optimization Methods for Large-Scale 5G and Beyond Wireless Communications Networks
Abstract: Existing optimization and deep learning approaches for the optimal design of large-scale 5G and beyond wireless communication networks often struggle to balance performance and computation time. In this talk, we introduce AI-assisted optimization methods that elegantly combine optimization and deep learning techniques. First, we present a novel AI-assisted optimization method for beamforming and power control in a large-scale OFDM-MIMO network. Then, we present a novel AI-assisted optimization method for activity detection in grant-free access for mMTC and uRLLC. These AI-assisted optimization methods involve designing parallel iterative algorithms with closed-form per-iteration updates, unrolling these parallel algorithms into neural networks with the algorithm parameters as tunable parameters optimized through network training, and creating DNNs to effectively select good initial points for these iterative algorithms. Numerical results demonstrate that the proposed AI-assisted optimization methods achieve superior tradeoffs between performance and computation time, emphasizing their significant value for 5G and beyond.

Biodata: Dr. Ying Cui received her B.Eng degree in Electronic and Information Engineering from Xi’an Jiao Tong University, China, in 2007 and her Ph.D. from the Hong Kong University of Science and Technology, Hong Kong SAR, China, in 2012. She held visiting positions at Yale University, US, in 2011 and Macquarie University, Australia, in 2012. From June 2012 to June 2013, she was a postdoctoral research associate at Northeastern University, US. From July 2013 to December 2014, she was a postdoctoral research associate at the Massachusetts Institute of Technology, US. From January 2015 to July 2022, she was an associate professor at Shanghai Jiao Tong University, China. Since August 2022, she has been an associate professor with the IoT Thrust at The Hong Kong University of Science and Technology (Guangzhou), China. She has published over 90 papers in prestigious IEEE journals and 85 papers in leading IEEE conferences. She was selected to the National Young Talent Program in 2014 and the World's Top 2% Scientists for the Years 2020-2025. She received Best Paper Awards from IEEE ICC 2015 and IEEE GLOBECOM 2021. She serves as an Editor for the IEEE Transactions on Wireless Communications (2018-2024) and the IEEE Transactions on Communications (2025-now).

Dr. Zezhong Zhang
The Chinese University of Hong Kong, Shenzhen, China

Speech Title: AI-Empowered Environment-Aware Radio Map Construction
Abstract: In the 6G era, real-time radio resource monitoring and management demand efficient radio map construction to track signal coverage and radio resource distribution. Traditional methods face challenges such as low resolution and high computational complexity. Advances in AI, particularly deep learning and generative models (e.g., GANs, diffusion models), now enable high-quality radio map generation by leveraging multi-model feature extraction and fusion. These techniques draw parallels with image generation, offering scalable solutions for radio map construction. We explore their technical implementations and future potential, concluding with a practical system platform that incorporates real measurements into the proposed AI-based method for accurate and real-time radio map estimation.

Biodata: Dr. Zezhong Zhang received his Bachelor's degree from the Southern University of Science and Technology (SUSTech) in 2017 and his Ph.D. from The University of Hong Kong (HKU) in 2021. He joined the School of Science and Engineering at CUHK-Shenzhen as a Research Assistant Professor in 2024. His research focuses on edge learning, radio map estimation, and B5G technologies including integrated sensing and communication (ISAC) and massive MIMO networks.

Dr. Tong Zhang
Harbin Institute of Technology, Shenzhen, China

Speech Title: Indoor Fluid Antenna Systems Enabled by Layout-Specific Modeling and Group Relative Policy Optimization
Abstract: The fluid antenna system (FAS) revolutionizes wireless communications by employing position-flexible antennas that dynamically optimize channel conditions and mitigate multipath fading. This innovation is particularly valuable in indoor environments, where signal propagation is severely degraded due to structural obstructions and complex multipath reflections. In this paper, we study the channel modeling and joint optimization of antenna positioning, beamforming, and power allocation for indoor FAS. In particular, we propose, for the first time, a layout-specific channel model and a novel group relative policy optimization (GRPO) algorithm for indoor FAS. Compared to the state-of-the-art Sionna model, our approach achieves an 83.3% reduction in computation time with an approximately 3 dB increase in root-mean-square error (RMSE). When simplified to a two-ray model, our channel model enables a closed-form solution for the optimal antenna position, achieving near-optimal performance. For the joint optimization problem, the proposed GRPO solution outperforms proximal policy optimization (PPO) and other baselines in sum-rate, while requiring only 49.2% computational resources of PPO, due to its group-based advantage estimation. Simulation results reveal that increasing either the group size or trajectory length in GRPO does not yield significant improvements in sum-rate, suggesting that these parameters can be selected conservatively without sacrificing performance.

Biodata: Dr. Tong Zhang hold a Ph.D. from The Chinese University of Hong Kong and completed postdoctoral training at the Southern University of Science and Technology. I have over 40 SCI/EI papers, including publications in renowned journals such as IEEE TIT, TCOM, and TWC. I received the Best Paper Award at the 31st Wireless and Optical Communications Conference (WOCC 2022), the 2024 Outstanding Paper Award by the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, and the IEEE WCL 2022 Examplary Reviewer Award.