Prof. Jun WANG

IEEE Fellow, IAPR Fellow, CAAI Fellow, Fellow of the Hong Kong Academy of Engineering

City University of Hong Kong

Speech Title: The Advances in Neurodynamic Optimization

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Jun Wang is a chair professor in the Department of Computer Science and the Department of Data Science at City University of Hong Kong. Prior to this position, he held various academic positions at Dalian University of Technology, Case Western Reserve University, University of North Dakota, and the Chinese University of Hong Kong. He also held various short-term visiting positions at USAF Armstrong Laboratory, RIKEN Brain Science Institute, Dalian University of Technology, Huazhong University of Science and Technology, and Shanghai Jiao Tong University. He published over 300 journal papers, 15 book chapters, 11 edited books, and numerous conference papers in these areas. He is the Editor-in-Chief of the IEEE Transactions on Artificial Intelligence and was the Editor-in-Chief of the IEEE Transactions on Cybernetics. He was an organizer of several international conferences, such as the General Chair of the 13th International Conference on Neural Information Processing (2006) and the 2008 IEEE World Congress on Computational Intelligence. He is an IEEE Fellow, IAPR Fellow, CAAI Fellow, a Fellow of the Hong Kong Academy of Engineering, a foreign member of Academia Europaea. He is a recipient of an IEEE Transactions on Neural Networks Outstanding Paper Award and APNNA Outstanding Achievement Award in 2011, Neural Networks Pioneer Award from IEEE Computational Intelligence Society in 2014, and Norbert Wiener Award from IEEE Systems, Man and Cybernetics Society in 2019, among others.

More speakers to be announced.

ICMLSC 2025 Keynote Speakers

Prof. Guandong Xu

IET Fellow

The Education University of Hong Kong, China

Guandong Xu is a full Professor in Data Science at the School of Computer Science and Data Science Institute, University of Technology Sydney, with PhD degree in Computer Science. His research interests cover Data Science, Recommender Systems, User Modelling, and Social Computing. He has published three monographs in Springer and CRC Press, and 220+ journal and conference papers, including TOIS, TKDD, TKDE, TNNLS, TCYB, TMM, TSE, TSC, TIFS, VLDB, IJCAI, AAAI, SIGMOD, KDD, SIGIR, CVPR, NIPS, ICML, WWW, WSDM, ICDM, ICDE, ICSE, and FSE conferences. He is the Editor-in-Chief of Human-centric Intelligent Systems and the assistant Editor-in-Chief of World Wide Web Journal. He has been serving on the editorial board or as a guest editor for several international journals, such as TOIS, TII, TCSS, PR etc. He has received several Awards from the academic and industry community. He is elevated as a Fellow of the Institute of Engineering and Technology (IET) and Australian Computer Society (ACS) in 2022 and 2021, respectively.

Prof. Kenji Suzuki

Tokyo Institute of Technology, Japan

Speech Title: Small-Data Deep Learning for AI-Aided Diagnosis and Virtual AI Imaging

Kenji Suzuki, Ph.D. worked at Hitachi Medical Corp, Aichi Prefectural University, Japan, as a faculty member, in Department of Radiology, University of Chicago, as Assistant Professor, and Medical Imaging Research Center, Illinois Institute of Technology, as Associate Professor (Tenured). He is currently a Full Professor (Tenured) & Founding Director of Biomedical Artificial Intelligence Research Unit, Institute of Innovative Research, Tokyo Institute of Technology, Japan. He published more than 395 papers (including 125 peer-reviewed journal papers). He has been actively researching on deep learning in medical imaging and AI-aided diagnosis in the past 25 years, especially his early deep-learning model was proposed in 1994. His papers were cited more than 16,000 times, and his h-index is 62. He is inventor on 37 patents (including ones of earliest deep-learning patents), which were licensed to several companies and commercialized via FDA approvals. He published 16 books and edited 20 journal special issues. He has been awarded numerous grants including NIH, NEDO, and JST grants, totaling $8M. He serves as Editors of more than 20 leading international journals including Pattern Recognition and AI. He chaired 110 international conferences. He is a Fellow of IARIA. He received 25 awards, including 3 Best Paper Awards in leading journals.

Prof. Kazutoshi Sasahara

School of Environment and Society, Institute of Science Tokyo, Japan

Speech Title: Countering Fake News: Computational Social Science Approaches

Kazutoshi Sasahara received his Ph.D. from the Graduate School of Arts and Sciences, The University of Tokyo in 2005. He held positions as Assistant Professor and Lecturer at the Graduate School of Informatics, Nagoya University, and Associate Professor and Professor at the School of Environment and Society, Tokyo Institute of Technology. Currently, he is a Professor at the School of Environment and Society, Institute of Science Tokyo. He is also a Visiting Professor at the National Institute of Informatics. His expertise is in computational social science, with a focus on the science of fake news. He received the Excellence Award in the Social Sciences Category of the DOCOMO Mobile Science Award in 2024. His major books include “The Science of Fake News: Understanding the Mechanisms of Spreading Misinformation, Conspiracy Theories, and Propaganda” (Kagaku-Dojin, in Japanese) and “The Impact of Deepfakes: AI Technology's Destruction and Creation” (PHP Institute, in Japanese).