Prof. Shiping Wang, Fuzhou University, China

Speech Title: Geometric Graph Convolutional Networks: From Paradigm to Application

 

Shiping Wang is currently working as a Full Professor with the College of Computer and Data Science, and the director of the Fujian Provincial Key Laboratory of Intelligent Metro, Fuzhou University, Fuzhou, China. He received his Ph.D. degree from the School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China in 2014. He was a Visiting Scholar in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada from August 2013 to August 2014. He worked as a Research Assistant in National University of Singapore from January 2014 to August 2014, and a Research Fellow in Nanyang Technological University of Singapore from August 2015 to August 2016. He was also a visiting researcher in the School of EECS, Peking University, Beijing, China from August 2019 to August 2020. His research interests include machine learning, deep learning, feature representation and granular computing.
He has authored or co-authored over 120 papers with more than 2500 citations (h-index as 26, i10-index as 54) in top conferences and journals, including T-PAMI, TIP, TMM, TSMC, TSP, TITS, TNSE, TCSS, TCSVT, TKDD, CVPR, AAAI, ACM MM, InFu, PR, NN, INS, KBS, etc. He has severed as the Regional Chair of the 10th Pacific-Rim Symposium on Image and Video Technology and IEEE International Conference on Digital Twins and Parallel Intelligence (DTPI), General Chair of the 2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI 2023) and the Session Chair of the 2023 IJCAI Young Elite Symposium (IJCAI YES 2023). He is also the PC member or reviewer of IJCAI, AAAI, IEEE TPAMI, IEEE TIP, IEEE TMM, IEEE TCSVT, Information Sciences, etc. He has been funded by the National Natural Science Foundation of China for several research projects.