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