Prof. Changxin Gao, Huazhong University of Science and Technology, China

Changxin Gao is a Professor at Huazhong University of Science and Technology. He received the Ph.D. degree in pattern recognition and intelligent systems from Huazhong University of Science and Technology, Wuhan, China, in 2010, under the supervision of Prof. Nong Sang. From 2012 to 2013, I was a researcher assistant in ICTEAM at Université Catholique de Louvain with Prof. Benoit Macq. His research interests focus on computer vision, deep learning, and multimodal understanding, with a special focus on semantic segmentation, multi-agent collaborative perception. He has published a series of high-quality papers in major journals and conferences such as IEEE T-PAMI, IEEE T-IP, CVPR, ICCV, ECCV, NeurIPS, AAAI. His/Her work has been recognized for its contributions to improving the accuracy, efficiency, and generalization ability of visual understanding models. He has served as a technical program committee member and reviewer for numerous leading conferences and journals.

Prof. Lei Zhang, Chongqing University, China

Lei Zhang, Professor and Ph.D. advisor at the School of Microelectronics and Communication Engineering, Chongqing University, Director of the Chongqing Key Laboratory of “Bio-sensing and Multimodal Intelligent Information Processing,” Leader of the “Visual Intelligence and Learning” Research Team at Chongqing University, National High-Level Young Talent, recipient of the third batch of the Ministry of Human Resources and Social Security’s “Xiangjiang Scholars” Program, recipient of the Chongqing Outstanding Young Scientists Fund, recipient of the Chongqing Special Support Program for High-Level Talents, and listed on both the “Lifetime Scientific Impact” and “Annual Scientific Impact” lists of the top 2% of scientists worldwide published by Stanford University. His research focuses on multimodal artificial intelligence, computer vision, robust machine learning, efficient transfer learning for large models, and vision-language large models. He has led more than 20 research projects funded by the Organization Department of the CPC Central Committee’s High-Level Talent Program, the Ministry of Science and Technology’s National Key Research and Development Program, the National Natural Science Foundation of China, the Ministry of Human Resources and Social Security’s Talent Programs, the Chongqing Outstanding Young Scientists Fund, and leading national enterprises. He has published over 160 academic papers in IEEE Transactions and Class A journals, including TPAMI, IJCV, CVPR, ICCV, ECCV, ICML, and AAAI. including 10 ESI top 1% highly cited papers. He has published one academic monograph, has been cited over 10,000 times on Google Scholar, and holds nearly 20 invention patents. He has received the Wu Wenjun Artificial Intelligence Natural Science Award, the Wu Wenjun Artificial Intelligence Outstanding Young Scholar Award, the Chongqing Natural Science Award, the Chongqing Top Ten Young Scientists in Science and Technology Award, the Huawei Spark Award, the Huawei Outstanding Project Achievement Award, the ACM SIGAI Rising Star Award, and the CCBR Best Paper Award, among others.

Prof. Yuexing Han, Shanghai University, China

Yuexing Han is currently a Professor and Doctoral/Master Supervisor at the School of Computer Engineering and Science, Shanghai University. He is a recipient of the Shanghai Pujiang Talent Program, and an external Master Supervisor of Shanghai Polytechnic University. He previously worked as a Specially Appointed Researcher at Tokyo Institute of Technology, Japan (2013–2020). He is a Distinguished Member of the China Computer Federation (CCF Member ID: 41526D), Member of the Chinese Materials Research Society (Member ID: E490914632M), ACM Member, and a Delegate of the 13th Member Congress of the China Computer Federation (A038-Shanghai 2). He also serves as a Young Editorial Board Member of Journal of Materials Informatics. His research interests include material image processing, shape space theory, and material data analysis.