Distinguished Business Analytics Speaker Series: Towards Better Data Driven Decisions

Tuesday, October 22, 2019
11 a.m.-12 p.m.
120/121
Fairlane Center North (FCN)
(map)

Most people accept that we should make decisions based on the data.  But that is not enough in itself:  we must make "good" decisions.  In this talk, we will consider some properties of good decisions, such as fairness and stability.  We will then describe how to ensure that data driven decisions have these properties.

Speaker: H. V. Jagadish, PhD, Professor of Electrical Engineering and Computer Science, University of Michigan-Ann Arbor

H. V. Jagadish is the Bernard A. Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan-Ann Arbor and the Director of the Michigan Institute for Data Science.  Prior to 1999, he was Head of the Database Research Department at AT&T Labs, Florham Park, New Jersey.

Professor Jagadish is well-known for his broad-ranging research on information management and has approximately 200 major papers and 37 patents. He has been a fellow of the Association for Computing Machinery, the world's largest scientific and educational computing society, since 2003.  He has also been a fellow of the American Association for the Advancement of Science since 2018 and has served on the board of the Computing Research Association from 2009-2018.  In addition, he  has been Editor of the Morgan & Claypool Synthesis Lecture Series on Data Management (2016-present); Program Chair of the VLDB Conference (2014); Founding Editor-in-Chief of the Proceedings of the VLDB Endowment (2008-2014); a trustee of the VLDB (Very Large DataBase) foundation (2004-2009); Program Chair of the ISMB conference (2005); Program Chair of the ACM SIGMOD annual conference (1996); and an Associate Editor for the ACM Transactions on Database Systems (1992-1995).  His many awards include the ACM SIGMOD Contributions Award in 2013 and the David E Liddle Research Excellence Award, at the University of Michigan, in 2008.  His popular MOOC on Data Science Ethics is available on both EdX and Coursera.

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Charu Chandra

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