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Department of Computer Science Distinguished Lecture
2015 Series

Big Data for Everyone

Prof. Jian Pei
School of Computing Science
Simon Fraser University

Date: June 18, 2015 (Thursday)
Time: 4:00 - 5:00 pm
Venue: RRS905, Sir Run Run Shaw Building, Ho Sin Hang Campus

Big Data post grand opportunities and challenges for egocentric analytics on Big Data. In this talk, I will discuss several interesting problems centered on egocentric queries and analysis on Big Data. We want to answer a series of natural questions imperative in several killer applications, such as “How is this patient similar to or different from the other Type II diabetes patients in the database?”, “How is University X distinct from the other universities?”, and “How is this residential property distinct from the others available in the market?” To answer such questions on Big Data, we have to search data of high dimensionality and high volume, and possibly of high dynamics as well. I will present some preliminary research results and some application case studies we obtained recently, as well as more challenges we identified.

Jian Pei is currently the Canada Research Chair (Tier 1) in Big Data Science and a professor at the School of Computing Science and the Department of Statistics and Actuarial Science at Simon Fraser University, Canada. He received his Ph.D. degree at the same school in 2002 under Dr. Jiawei Han’s supervision. His research interests are to develop effective and efficient data analysis techniques for novel data intensive applications. He has published prolifically and is one of the top cited authors in data mining. He received a series of prestigious awards. He is also active in providing consulting service to industry and transferring the research outcome in his group to industry and applications. He is an editor of several esteemed journals in his areas and a passionate organizer of the premier academic conferences defining the frontiers of the areas. He is an IEEE Fellow.

********* ALL INTERESTED ARE WELCOME ***********
(For enquiry, please contact Computer Science Department at 3411 2385)
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