报告题目: Complex Data Learning for Knowledge Discovery

报告人：Zhongfei Zhang Professor

报告时间：2019年12月18日（周三）16：00

报告地点：逸夫楼C座603会议室

摘要：

Complex data include almost all the data scenarios we encounter everyday and also we face in many real-world applications. The specific examples in complex data learning for knowledge discovery include problems in social network analysis, natural language understanding and visual data understanding, as well as problems in noisy data learning.

报告人简介：

Zhongfei Zhang is a professor at Computer Science Department, State University of New York (SUNY) at Binghamton, USA, and the director of the Multimedia Research Laboratory in the Department. He was QiuShi Chair Professor at the Department of Information Science and Electronics Engineering, Zhejiang University, China, when he was on leave from Binghamton. 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. He was on the faculty of Computer Science and Engineering Department at SUNY Buffalo, before he joined the faculty of computer science at SUNY Binghamton. He is the author of the very first monograph on multimedia data mining and the very first monograph on relational data clustering. He holds more than thirty inventions, has served as members of organization committees of several premier international conferences in his areas, and as editorial board members for several international journals. He has served as a French CNRS Chair Professor of Computer Science at the University of Lille 1 in France, a JSPS Fellow in Japan, as well as several visiting professorships from many universities in the world. He has also served as technical consultants for a number of industrial and governmental organizations. He received many honors including premier conference best paper awards, SUNY Chancellor’s Award for Scholarship and Creative Activities, and SUNY Chancellor’s Promising Inventor Award. He is an IEEE Fellow.