CCAT 2022 Keynote Speakers
Prof. Jun Fu
Northeastern University, China
付俊 教授, 东北大学
未来技术学院院长，机器人学院常务副院长
Jun Fu received the Ph.D. degree in mechanical engineering from Concordia University, Montreal, Canada, in 2009. He is a postdoctoral researcher in the department of mechanical engineering, Massachusetts Institute of Technology (MIT), USA from 2010 to 2014. He is Dean of School of Future Technologies, and Executive Dean of Faculty of Robot Science and Engineering, Northeastern University, China. His current research is on dynamic optimization, switched systems, and constructive control. He has authored/co-authored over 100 publications, over 40 of which appeared in IEEE/IFAC journals. He is a winner of China National Funds for Distinguished Young Scientists (NSFC), and also a Changjiang Scholar Chair professor. He won the 2018 Young Scientist Award in Science from MOE, China. He is Associate Editor of IEEE Trans. on Industrial Informatics, IEEE Transactions on Neural Networks and Learning Systems, Control Engineering Practice (IFAC), and Journal of Industrial and Management Optimization.
Prof. Dianhui Wang
China University of Mining and Technology, China
王殿辉 教授, 中国矿业大学
Prof. Wang was awarded a PhD from Northeastern University, Shenyang, China, in 1995. From 1995 to 2001, he worked as a Postdoctoral Fellow at Nanyang Technological University, Singapore, and a Research Fellow at The Hong Kong Polytechnic University, Hong Kong, China. From July 2001 to December 2020, he worked as a Reader and Associate Professor with the Department of Computer Science and Information Technology, La Trobe University (LTU), Australia, and currently with adjunct appointment. Since 2017, Dr Wang has been an adjunct Professor at State Key Laboratory of Synthetical Automation of Process Industries, Northeastern University (NEU), China. In July 2021, He joined AI Research Institute (AIRI) at China University of Mining and Technology (CUMT), working as a Professor, Dean of AIRI, and Director of the Research Center for Stochastic Configuration Machines. His current research focuses on industrial data-oriented machine learning theory and applications, specifically on Deep Stochastic Configuration Networks (DeepSCNs) for data analytics in process industries, intelligent sensing systems and power engineering.
Prof. Wang published more than 240 technical papers on applied mathematics, control engineering and computer sciences. He is the creator of DeepSCN model with innovative patent in Australia, and serving as the Editor-in-Chief of Industrial Artificial Intelligence (Springer), an Associate Editor for IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, Information Sciences, and WIREs Data Ming and Knowledge Discovery.
Prof. Yan Wu
Georgia Southern University, USA
吴岩 教授, 美国乔治亚南方大学
Dr. Wu received the B.S. degree in Mathematics and Computer Science from Beijing University of Technology in 1992, the M.S. degree in Applied Mathematics and Ph.D. in Applied Mathematics and Electrical Engineering both from University of Akron in 1996 and 2000, respectively.
In 2000, he joined Georgia Southern University as an assistant professor in the Department of Mathematical Sciences, where he is currently a full professor in Mathematics. He is also an adjunct research professor of the Department of Mechanical Engineering, University of Manitoba, Winnipeg, Canada. His research interests include adaptive control, active disturbance rejection control, decentralized control, digital filter design, sampling theory and feature extractions, smart grid power systems, hydraulic systems, internal leakage prognosis with neural network, Tumor Models for Cancer Immunotherapy. He has two patents granted by the United States Patent and Trademark Office.