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【科苑经管国际学术论坛】Broad Learning System: An effective and efficient incremental learning system without the need for deep architecture(6月28日)
发布时间:2017/6/26

科苑经管国际学术论坛第20期

 

报告题目:Broad Learning System: An effective and efficient incremental learning system without the need for deep architecture

 

报告人:Philip Chen,Dean and Chair Professor, Faculty of Science and Technology, University of Macau
 

报告时间:2017年6月28日(周三)上午9:30—11:00
 

报告地点:中国科学院大学中关村校区青年公寓7号楼4楼会议室
 

报告人简介:C. L. Philip Chen received the M.S. degree in electrical engineering from the University of Michigan, Ann Arbor, in 1985 and the Ph.D. degree in electrical engineering from Purdue University, West Lafayette, IN, in 1988.
 

Currently, he is the Dean of the Faculty of Science and Technology, University of Macau, Macau, China and a Chair Professor of the Department of Computer and Information Science after spending at U.S. for 28 years as a tenured professor, as a department head and associate dean in two different universities. His research area is in systems, cybernetics, and computational intelligence. Dr. Chen is a Fellow of the IEEE, AAAS, Chinese Association of Automation, and HKIE. He was the President of IEEE Systems, Man, and Cybernetics Society (2012-2013). Currently, he is the Editor-in-Chief of IEEE Transactions on Systems, Man, and Cybernetics: Systems (2014- ) and an associate editor of several IEEE Transactions. He is also the Chair of TC 9.1 Economic and Business Systems of IFAC (International Federation of Automatic Control). In addition, he is an ABET (Accreditation Board of Engineering and Technology Education) Program Evaluator for Computer Engineering, Electrical Engineering, and Software Engineering programs.