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.