Professor Philip S. Yu

An American computer scientist and Professor of Information Technology at the University of Illinois at Chicago, he is known for his work in the field of data mining. He received his B.S. degree in Electrical Engineering from the National Taiwan University, and his M.S. and Ph.D. degrees, also in Electrical Engineering, from Stanford University in Stanford, California in 1978; and received an M.B.A. degree from New York University in 1982. He began his career at IBM?s Thomas J. Watson Research Center, where he eventually became Manager of the Software Tools and Techniques group. At IBM, the focus of his project included the development of advanced algorithms and optimization techniques for data mining, anomaly detection and personalization, and the enabling of Web technologies to facilitate E-commerce and pervasive computing. Currently he is Distinguished Professor and Wexler Chair in Information Technology at the Department of Computer Science of the University of Illinois at Chicago. His research interests are in the fields of data mining (especially on graph/network mining), social network, privacy preserving data publishing, disk arrays, computer architecture, performance modeling and workload analysis, data stream, database systems, and Internet applications and technologies. He is an ISI Highly Cited researcher. According to Google Scholar he is among the ten highest ranked living American computer scientists. An IBM Master Inventor, he holds over 300 U.S. patents. From 2001 to 2004, he was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering and he is currently Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data. He is the recipient of several awards by IBM. He received an IEEE Region 1 Award for "promoting and perpetuating numerous new electrical engineering concepts" and he received the 2013 IEEE Technical Achievement Award, "For pioneering and fundamentally innovative contributions to the scalable indexing, querying, searching, mining and anonymization of big data". He is an ACM Fellow and IEEE Fellow. He has chaired numerous conferences including serving on the Steering Committee of IEEE Intl. Conference on Data Mining. He has published several books and over 650 articles a few of which include: with Park, Jong Soo, and Ming-Syan Chen, An effective hash-based algorithm for mining association rules, Vol. 24. No. 2. ACM, 1995; with Chen, Ming-Syan and Jiawei Han, "Data mining: an overview from a database perspective", Knowledge and data Engineering, IEEE Transactions on 8.6 (1996): 866-883; and with Ross Quinlan, Qiang Yang, Zhou Zhihua and David Hand et al, Top 10 algorithms in data mining, Knowledge and Information Systems 14.1: 1-37, 2008.