Keynote Speakers
Prof. Ting-Chung Poon
(IEEE/IOP/SPIE Fellow)
Virginia Polytechnic Institute and State University, USA
Ting-Chung Poon is a Professor of Electrical and Computer
Engineering at Virginia Tech, Virginia, USA. His current
research interests include Information Optics, 3-D image
processing and Optical Scanning Holography (OSH). Dr. Poon
is the author of the monograph Optical Scanning Holography
with MATLAB (Springer, 2007), and is the co-author of, among
other textbooks, Modern Information Optics with MATLAB
(Cambridge University Press and Higher Education Press,
China, 2023) and Introduction to Modern Digital Holography
with MATLAB (Cambridge University Press, 2014). He is also
Editor of the book Digital Holography and Three-Dimensional
Display (Springer, 2006). Dr. Poon served as Division Editor
of Applied Optics from 2008 to 2014, and was Associate
Editor-in-Chief of Chinese Optics Letters. He also served as
Associate Editor of the IEEE Transactions on Industrial
Informatics and was General Chair of Optica Annual Meeting
Frontier in Optics + Laser Science (FiO LS) for the years
2021 and 2022. Currently, Prof. Poon is Specialty Chief
Editor of Frontiers in Photonics, and Editor of Applied
Sciences.
Dr. Poon is a Life Fellow of the IEEE, a Fellow of the
Institute of Physics (IOP), the Optica, and the
International Society for Optics and Photonics (SPIE). He
received the 2016 Dennis Gabor Award of the SPIE for his
pioneering contributions to optical scanning holography
(OSH). Dr. Poon was a Visiting Professor for Senior
International Scientists at the Shanghai Institute of Optics
and Fine Mechanics, Chinese Academy of Science, a Visiting
Professor at Shizuoka University (Hamamatsu, Japan), Nihon
University (Japan), National Taiwan Normal University
(Taiwan), and City University of Hong Kong (China).
Currently, he is a Visiting Professor at Shanghai
University, an Adjunct Professor at National Central
University (Taiwan) and a Distinguished Chair Professor of
Feng Chia University (Taiwan).
Prof. Jie Lu
(IEEE/IFSA Fellow)
University of Technology Sydney, Australia
Distinguished Professor Jie Lu is a world-renowned scientist
in the field of computational intelligence, primarily known
for her work in fuzzy transfer learning, concept drift,
recommender systems, and decision support systems. She is an
IEEE Fellow, IFSA Fellow, Australian Computer Society
Fellow, and Australian Laureate Fellow. Professor Lu is the
Director of the Australian Artificial Intelligence Institute
(AAII) at University of Technology Sydney (UTS), Australia.
She has published six research books and over 500 papers in
leading journals and conferences; won 10 Australian Research
Council (ARC) Discovery Projects and over 20 industry
projects as leading chief investigator; and supervised 50
PhD students to completion. Prof Lu serves as
Editor-In-Chief for Knowledge-Based Systems and
International Journal of Computational Intelligence Systems.
She is a recognized keynote speaker, delivering over 40
keynote speeches at international conferences. She is the
recipient of two IEEE Transactions on Fuzzy Systems
Outstanding Paper Awards (2019 and 2022), NeurIPS
Outstanding Paper Award (2022), Australia's Most Innovative
Engineer Award (2019), Australasian Artificial Intelligence
Distinguished Research Contribution Award (2022), Australian
NSW Premier's Prize on Excellence in Engineering or
Information & Communication Technology (2023), and the
Officer of the Order of Australia (AO) in the Australia Day
2023.
Speech Title: "Fuzzy Machina Learning"
Abstract: The talk will present the concept,
framework, methods, and algorithms of fuzzy machine learning
and how the new techniques can effectively learn from data
to support data-driven prediction and decision-making in
uncertain, complex, and dynamic situations. It will firstly
present classical fuzzy machina learning. It will then
introduce the concepts and advanced methods of fuzzy
transfer learning and fuzzy drift learning respectively.
Finally, it will talk about the applications of fuzzy
machine learning in practice.
Prof. Xizhao Wang
(IEEE/CAAI Fellow)
Shenzhen
University, China
Xizhao Wang received his PhD from Harbin
Institute of Technology in 1998. He is currently a professor
at college of computer science in Shenzhen University.
Previously he was the dean of computer science college in
Hebei university from 2000 to 2014.
Prof. Wang’s current research interests include
uncertainty-aware machine learning and lightweight of large
language model. He pioneered the research on Machine
Learning in uncertain environment, and published several
monographs and textbooks, and over 300 research papers at
conferences and in journals. His works have been cited
14,178 times according to Google scholar in 2023. He was on
the list of Highly Cited Researchers by Clarivate in 2019
and 2020, in recognition of exceptional research performance
demonstrated by production of multiple highly cited papers
that rank in the cross-field top 1%.
Prof. Wang is an IEEE Fellow (2012), a CAAI Fellow (2017),
and the Editor-in-Chief of Springer Journal Machine Learning
and Cybernetics (from 2010 to present).
Prof.
Xinwang Liu
National University of Defense Technology, China
Xinwang Liu received his PhD degree from National University of Defense Technology (NUDT), China, in 2013. He is now Professor at School of Computer, NUDT. His current research interests include kernel learning, multi-view clustering and unsupervised feature learning. Dr. Liu has published 120+ peer-reviewed papers, including those in highly regarded journals and conferences such as IEEE T-PAMI, IEEE T-KDE, IEEE T-IP, IEEE T-NNLS, IEEE T-MM, IEEE T-IFS, ICML, NeurIPS, CVPR, ICCV, AAAI, IJCAI, etc. He is an Associate Editor of IEEE T-NNLS, IEEE TCYB and Information Fusion Journal. More information can be found at https://xinwangliu.github.io/.