Keynote Speakers

Prof. Acm Fong
Western Michigan University, USA

A.C.M. Fong was appointed professor of computer science at Auckland University of Technology in 2008. Since leaving AUT in 2013, he has been with University of California Irvine, University of Glasgow, and now Western Michigan University. His research interests revolve around data-driven knowledge discovery and aspects of artificial intelligence, such as machine learning for classification and ontological knowledge representation and reasoning. His scientific contributions include two books, fourteen book sections, two international patents, and circa 230 papers in reputable journals and conference proceedings. Leading journals that carry his work include IEEE T-KDE, IEEE T-ITBiomed, IEEE T-MM, IEEE T-Evolutionary Computing, IEEE T-Affective Computing, IEEE T-II, and several other IEEE Transactions titles. He has served on several journal editorial boards and numerous conference committees. Dr. Fong holds four degrees in EE and CS. He is a registered Chartered Engineer and European Engineer.




Prof. Zhisheng Niu
IEEE Fellow
Tsinghua University, China

Zhisheng Niu graduated from Beijing Jiaotong University, China, in 1985, and got his M.E. and D.E. degrees from Toyohashi University of Technology, Japan, in 1989 and 1992, respectively. During 1992-1994, he worked for Fujitsu Laboratories Ltd., Japan, and in 1994 joined with Tsinghua University, Beijing, China, where he is now a professor at the Department of Electronic Engineering. During 1997-1998, he visited Hitachi Central Research Laboratory as a HIVIPS senior researcher. His major research interests include queueing theory and traffic engineering, wireless communications and mobile Internet, vehicular communications and smart networking, and green communication and networks.
Dr. Niu has been serving IEEE Communications Society since 2000, first as Chair of Beijing Chapter and then as Director of Asia-Pacific Board, Director for Conference Publications, Chair of Emerging Technologies Committee, and Director for Online Contents. He has also served as editor of IEEE Wireless Communication, associate Editor-in-Chief of IEEE/CIC joint publication China Communications, and Editor-in-Chief of IEEE Trans. Green Commun. & Networks. He received the Outstanding Young Researcher Award from Natural Science Foundation of China in 2009, Best Paper Awards from IEEE Communication Society Asia-Pacific Board in 2013 and from Journal of Communications and Information Networks (JCIN) in 2019, Distinguished Technical Achievement Recognition Award from IEEE Communications Society Green Communications and Computing Technical Committee in 2018, and Harold Sobol Award for Exemplary Service to Meetings & Conferences from IEEE Communication Society in 2019. He was selected as a distinguished lecturer of IEEE Communication Society as well as IEEE Vehicular Technologies Society. He is a fellow of both IEEE and IEICE.

 

Speech Title "Robust, Reliable, and Resilient Cooperative Perception for Connected Autonomous Driving"

Abstract: Environmental perception is fundamental to safe and efficient autonomous driving. With Cooperative Perception (CP) enabled by V2X networks, connected vehicles can exchange perceptual information to see through blind zones and deal with long-tail scenarios. In this talk, we propose a robust, reliable, and resilient CP framework for connected autonomous driving. First, for robustness to localization error and communication delay, a calibration-free two-stage CP paradigm is proposed using deep metric learning. This fusion method only requires image data and is adaptive to the transmission rate. Then, to guarantee high reliability, hard AoI constraints are considered in sensor scheduling of CP to guarantee the timeliness of perceptual information. The required channel resources are minimized in asynchronous status update settings. Next, to resiliently adapt to the dynamic traffic environment, we propose a learning-while-scheduling approach to trade off exploration and exploitation. An online sensor scheduling algorithm is designed based on restless MAB (Multi-Armed Bandit) theory to maximize the average CP gain with low scheduling overhead. Finally, a large-scale multi-view multi-modality dataset, called Dolphins, is presented to assist further researches and verification of CP systems.

 

Prof. Wen-Huang Cheng
IEEE Fellow, IET Fellow
National Taiwan University, Taiwan

Wen-Huang Cheng is a University Distinguished Chair Professor in the Department of Computer Science and Information Engineering at National Taiwan University. His current research interests include multimedia, computer vision, and machine learning. He has actively participated in international events and played significant leadership roles in prestigious journals, conferences, and professional organizations. These roles include serving as Editor-in-Chief for IEEE CTSoc News on Consumer Technology, Senior Editor for IEEE Consumer Electronics Magazine (CEM), Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and IEEE Transactions on Multimedia (TMM), General Chair for ACM MMAsia (2023), IEEE ICME (2022), and ACM ICMR (2021), Chair for IEEE CASS Multimedia Systems and Applications (MSA) technical committee, and governing board member for IAPR. He has received numerous research and service awards, including the Best Paper Award at the 2021 IEEE ICME and the Outstanding Associate Editor Award of IEEE TMM (2021 and 2020, twice). He is an IEEE Fellow, IET Fellow, and ACM Distinguished Member.

 

Speech Title "Launching a New AI Era with Large Language Model (LLM) Agents"

Abstract: The frontier of artificial intelligence (AI) is expanding rapidly with the integration of Large Language Models (LLMs) into the domain of computer vision. This talk delves into the revolutionary impact of LLM agents in propelling us into a new AI era, leading to more intuitive and intelligent systems. A focal point of the talk will be on the ways LLM agents contribute to advanced computer vision tasks, such as image synthesis. We will also provide a glimpse into future developments, discussing the challenges and potential solutions in training, fine-tuning, and deploying LLM agents for optimal performance in complex environments.

 

 

Prof. Hoa Le Minh
Northumbria University, UK

Hoa Le Minh is currently a Professor in Optical Communications and the Deputy Head of Department of Mathematics, Physics, and Electrical Engineering, Northumbria University, UK. Previously he was a Research Fellow at University of Oxford, UK (2007-2010), a Research Assistant at Siemens AG, Munich, Germany (2002-2004), and a Lecturer in Telecommunications at Ho Chi Minh University of Technology, Vietnam (1999-2001). He is an expert in photonics, optical communications, visible light communications, smartphone technology, signal processing, and intelligent networks. He has published more than 200 articles, in journals, conferences, and book chapters, and received grants from EPSRC, Innovate UK, EU and industry.
Hoa was a former Chapter Chair of IEEE Communications Society (ComSoc) UK and Ireland Chapter. He is a member of EPSRC ICT grant prioritisation panels, and an associate editor for peer-review journals.