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Big Data: Challenges and Opportunities
Speaker: Professor H. V. Jagadish Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science University of Michigan Title: "Big Data: Challenges and Opportunities" Date: Monday, 19 November 2012 Time: 4:00pm - 5:00pm Venue: Lecture Theatre F (near lifts 25/26), HKUST Abstract: The promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.'' In fact, it is hard to avoid mention of Big Data anywhere we turn today. Yet, many have a very narrow interpretation of what that means, and we lose track of the fact that there are multiple steps to the data analysis pipeline, whether the data are big or small. At each step, there is work to be done, and there are challenges with Big Data ****************** Biography: H. V. Jagadish is Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science, and Director of the Software Systems Research Laboratory, at the University of Michigan in Ann Arbor. After earning his PhD from Stanford in 1985, he spent over a decade at AT&T Bell Laboratories in Murray Hill, N.J., eventually becoming head of AT&T Labs database research department at the Shannon Laboratory in Florham Park, N.J. He has also served as a Professor at the University of Illinois in Urbana-Champaign and as the Shaw Visiting Professor at the National University of Singapore. Professor Jagadish is well-known for his broad-ranging research on information management, and has approximately 200 major papers and 37 patents. He is a fellow of the ACM ("The First Society in Computing") and serves on the board of the Computing Research Association. He has been an Associate Editor for the ACM Transactions on Database Systems (1992-1995), Program Chair of the ACM SIGMOD annual conference (1996), Program Chair of the ISMB conference (2005), a trustee of the VLDB (Very Large DataBase) foundation (2004-2009), and Founding Editor-in-Chief of the Proceedings of the VLDB Endowment (since 2008).