IEEE Fellow

    Prof. James Tin-Yau Kwok, The Hong Kong University of Science and Technology, Hong Kong, China


BIO: Prof. Kwok is a Professor in the Department of Computer Science and Engineering, Hong Kong University of Science and Technology. Prof. Kwok served / is serving as an Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing, Artificial Intelligence Journal, International Journal of Data Science and Analytics, and Editorial Board Member of Machine Learning. He is also serving as Senior Area Chairs of major machine learning / AI conferences including NeurIPS, ICML, ICLR, and IJCAI. He is recognized as the Most Influential Scholar Award Honorable Mention for "outstanding and vibrant contributions to the field of AAAI/IJCAI between 2009 and 2019". He is an IEEE Fellow, and will be the IJCAI-2025 Program Chair.




Fellow of IEEE

Prof. Junsong Yuan, State University of New York at Buffalo, USA


BIO: Dr. Junsong Yuan is Professor and Director of Visual Computing Lab at Department of Computer Science and Engineering (CSE), State University of New York at Buffalo, USA. Before joining SUNY Buffalo, he was Associate Professor (2015-2018) and Nanyang Assistant Professor (2009-2015) at Nanyang Technological University (NTU), Singapore. He obtained his Ph.D. from Northwestern University in 2009 (advised by Prof. Ying Wu), M.Eng. from National University of Singapore in 2005, and B.Eng. from Huazhong University of Science Technology (HUST) in 2002. He received Chancellor's Award for Excellence in Scholarship and Creative Activities from SUNY, Nanyang Assistant Professorship from NTU, Outstanding EECS Ph.D. Thesis award from Northwestern University, and Best Paper Award from IEEE Trans. on Multimedia. He serves as Senior Area Editor of Journal of Visual Communication and Image Representation (JVCI), Associate Editor of IEEE Trans. on Pattern Analysis and Machine Intelligence (T-PAMI), IEEE Trans. on Image Processing (T-IP), IEEE Trans. on Circuits and Systems for Video Technology (T-CSVT), and Machine Vision and Applications (MVA). He also serves as General/Program Co-chair of ICME and Area Chair for CVPR, ICCV, ECCV, ACM MM, etc. He was elected Faculty Senator at Both SUNY Buffalo and NTU. He is a Fellow of IEEE and IAPR.




Fellow of IEEE, IAPR, and AAIA
Prof. Zhongfei (Mark) Zhang, Binghamton University State University of New York, USA


BIO: Zhongfei (Mark) Zhang is a professor at Computer Science Department, Binghamton University, State University of New York (SUNY), USA. He received a B.S. in Electronics Engineering (with Honors), an M.S. in Information Sciences, both from Zhejiang University, China, and a PhD in Computer Science from the University of Massachusetts at Amherst, USA. His research interests are in the broad areas of machine learning, data mining, computer vision, and pattern recognition, and specifically focus on multimedia/multimodal data understanding and mining. He was on the faculty of Computer Science and Engineering at the University at Buffalo, SUNY, before he joined the faculty of Computer Science at Binghamton University, SUNY. He is the author or co-author of the very first monograph on multimedia data mining and the very first monograph on relational data clustering. He has published over 200 papers in the premier venues in his areas. He holds more than thirty inventions, has served as members of the organization committees of several premier international conferences in his areas including general co-chair and lead program chair, and as editorial board members for several international journals. He served as a French CNRS Chair Professor of Computer Science at the University of Lille 1 in France, a JSPS Fellow in Chuo University, Japan, a QiuShi Chair Professor in Zhejiang University, China, as well as visiting professorships at many universities and research labs in the world when he was on leave from Binghamton University years ago. He received many honors including SUNY Chancellor’s Award for Scholarship and Creative Activities, SUNY Chancellor’s Promising Inventor Award, and best paper awards from several premier conferences in his areas. He is a Fellow of IEEE, IAPR, and AAIA.


Speech Title: On Deep Learning Reliability




Prof. Chi Man Pun, University of Macau, Macau, China


BIO: Prof. Pun received his Ph.D. degree in Computer Science and Engineering from the Chinese University of Hong Kong in 2002, and his M.Sc. and B.Sc. degrees from the University of Macau. He had served as the Head of the Department of Computer and Information Science, University of Macau from 2014 to 2019, where he is currently a Professor and in charge of the Image Processing and Pattern Recognition Laboratory. He has investigated many externally funded research Projects as PI, and has authored/co-authored more than 200 refereed papers in many top-tier Journals (including T-PAMI, T-IFS, T-IP, T-DSC, T-KDE, and T-MM) and Conferences (including CVPR, ICCV, ECCV, AAAI, ICDE, IJCAI, MM, and VR). He has also co-invented several China/US Patents, and is the recipient of the Macao Science and Technology Award 2014 and the Best Paper Award in the 6th Chinese Conference on Pattern Recognition and Computer Vision (PRCV2023). Dr. Pun has served as the General Chair for the 10th &11th International Conference Computer Graphics, Imaging and Visualization (CGIV2013, CGIV2014), the 13th IEEE International Conference on e-Business Engineering (ICEBE2016), and the General Co-Chair for the IEEE International Conference on Visual Communications and Image Processing (VCIP2020) and the International Workshop on Advanced Image Technology (IWAIT2022), and the Program/Local Chair for several other international conferences. He has also served as the SPC/PC member for many top CS conferences such as AAAI, CVPR, ICCV, ECCV, MM, etc. He is currently serving as the editorial board member for the journal of Artificial Intelligence (AIJ). Besides, he has been listed in the World's Top 2% Scientists by Stanford University since 2020. His research interests include Image Processing and Pattern Recognition; Multimedia Information Security, Forensic and Privacy; Adversarial Machine Learning and AI Security, etc. He is also a senior member of the IEEE.