Keynote Speakers  主讲嘉宾

Prof. WAH Wan-Sang Benjamin
IEEE Life Fellow/ACM Fellow/AAAS Fellow
The Chinese University of Hong Kong, Hong Kong, China

Bio: Benjamin W. Wah is Professor Emeritus at The Chinese University of Hong Kong (CUHK) and Franklin W. Woeltge Professor Emeritus of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC). He previously served as Provost and Wei Lun Professor of Computer Science and Engineering at CUHK. He held joint appointments as the Franklin W. Woeltge Endowed Professor of Electrical and Computer Engineering and Professor at the Coordinated Science Laboratory at UIUC. Professor Wah received his Ph.D. in Computer Science from the University of California, Berkeley. His research spans nonlinear search and optimization, multimedia technologies, and artificial intelligence. He has received numerous prestigious awards for his contributions to research and professional service, including the IEEE Computer Society W. Wallace McDowell Award (2006), Richard E. Merwin Award (2007), Tsutomu Kanai Award (2009), the Distinguished Alumni Award in Computer Science from UC Berkeley (2011), the Bronze Bauhinia Star from the Hong Kong SAR Government (2021), and the CUHK Honorary Fellow Award (2026). A pioneer in scholarly publishing, Professor Wah co-founded the IEEE Transactions on Knowledge and Data Engineering in 1988 and served as its Editor-in-Chief from 1993 to 1996. He is currently Co-Editor-in-Chief of Computers and Education: Artificial Intelligence and Honorary Editor-in-Chief of Knowledge and Information Systems. His leadership within the IEEE Computer Society includes serving as Vice President for Publications (1998–1999) and President (2001). Professor Wah is a Fellow of the AAAS and ACM, and a Life Fellow of the IEEE.

Speech Title: Perceptual Quality in Online Real-Time Multimedia: An AI Approach

Abstract: With the rapid advancement of multimedia technologies, a wide array of interactive online games and real-time multimedia applications (RIMAs) has emerged. However, user-perceived quality in these applications often suffers due to network delays, resulting in sluggish or unresponsive interactions. This presentation introduces a general framework for optimizing the perceptual quality of diverse online, real-time, interactive multimedia applications. We propose a machine learning-based offline-online framework that enables practical implementation and runtime optimization. In the offline stage, the framework decomposes complex multi-metric, multi-control problems into simpler subproblems, each evaluating perceptual quality based on a single metric and control variable. During the online stage, these learned models are integrated into a composite model that identifies optimal operating points, effectively overcoming the exponential complexity of direct optimization. To validate our approach, we present two case studies: two-party and multiparty videoconferencing, and multiparty online action games. Experimental results demonstrate significant improvements in perceptual quality, highlighting the effectiveness and generality of our solution.

 

Prof. Wenwu Wang
IEEE Fellow
University of Surrey, UK

Bio: Wenwu Wang is a Professor in Signal Processing and Machine Learning, Associate Head of External Engagement, School of Computer Science and Electronic Engineering, University of Surrey, UK. He is also an AI Fellow at the Surrey Institute for People Centred Artificial Intelligence. His current research interests include signal processing, machine learning/AI, and machine audition (listening). He has (co)-authored over 400 papers in these areas. His work has been recognized with more than 15 accolades, including the Meta Distinguished Faculty Award (2026), Audio Engineering Society Best Technical Paper Award (2025), IEEE Signal Processing Society Young Author Best Paper Award (2022), DCASE Judge’s Award (2020, 2023, and 2024), DCASE Reproducible System Award (2019 and 2020), and LVA/ICA Best Student Paper Award (2018). He has been elected to IEEE Fellow for contributions to audio classification, generation and source separation, since 2026. He is a Senior Area Editor (2025-2027) of IEEE Open Journal of Signal Processing and an Associate Editor (2024-2028) for IEEE Transactions on Multimedia. He was a Senior Area Editor (2019-2023) and Associate Editor (2014-2018) for IEEE Transactions on Signal Processing, and an Associate Editor (2020-2025) for IEEE/ACM Transactions on Audio Speech and Language Processing. He is the elected Chair (2025-2027) of the EURASIP Technical Area Committee on Acoustic Speech and Music Signal Processing, and a Board Member (2026-2028) of the IEEE Signal Processing Society (SPS) Conferences Board. He was the elected Chair (2023-2024) of IEEE SPS Machine Learning for Signal Processing Technical Committee and a Board Member (2023-2024) of IEEE SPS Technical Directions Board. He has been on the organising committee of INTERSPEECH 2022 and IEEE ICASSP 2019 & 2024. He has been an invited Keynote or Plenary Speaker on about 30 international conferences and workshops. More details about his works including relevant papers can be found from his personal page:
https://personalpages.surrey.ac.uk/w.wang/

 

Prof. Zhiguo Shi
IEEE Fellow, IET Fellow
Zhejiang University, China

Bio: Shi Zhiguo is a Qiushi Distinguished Professor and Doctoral Supervisor at Zhejiang University, a Changjiang Scholar Distinguished Professor appointed by the Ministry of Education, a Fellow of the Institute of Electrical and Electronics Engineers (IEEE Fellow), a Fellow of the Institution of Engineering and Technology (IET Fellow), and Vice Chairman of the Signal Processing Committee of the Chinese Institute of Electronics. He is also the Chief Scientist of a National Key Research and Development Program. Currently, he serves as Deputy Dean of the Office of Science and Technology Research at Zhejiang University and Executive Deputy Director of the Provincial Key Laboratory of Airspace Perception and Autonomous Unmanned Systems.