ICTIR 2015   September 27-30, 2015                                                Northampton, Massachusetts (USA)

ACM SIGIR International Conference on the Theory of Information Retrieval

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Keynote Speaker

Andrew McCallum

Director, Center for Data Science;
Director, Information Extraction and Synthesis Laboratory,
and Professor in the College of Information and Computer Sciences,
University of Massachusetts Amherst


"Embedded Representations of Lexical and Knowlege-Base Semantics"

Bio: Dr. Andrew McCallum is a Director of the Center for Data Science, Director of the Information Extraction and Synthesis Laboratory, and a Professor in the College of Information and Computer Sciences at University of Massachusetts Amherst.  He has published over 250 papers in many areas of AI, including natural language processing, machine learning, data mining and reinforcement learning, and his work has received over 40,000 citations.  He obtained his PhD from University of Rochester in 1995 with Dana Ballard and a postdoctoral fellowship from Carnegie Mellon University with Tom Mitchell and Sebastian Thrun.  In the early 2000's he was Vice President of Research and Development at at WhizBang Labs, a 170-person start-up company that used machine learning for information extraction from the Web.  He is an AAAI Fellow, the recipient of the UMass Chancellor's Award for Research and Creative Activity, The UMass Amherst Samuel F. Conti Faculty Fellowship, the UMass NSM Distinguished Research Award, the UMass Lilly Teaching Fellowship, and research awards from Google, IBM, Yahoo and Microsoft.  He was the General Chair for the International Conference on Machine Learning (ICML) 2012, and is the current president of the International Machine Learning Society, as well as member of the editorial board of the Journal of Machine Learning Research.
He and co-authors received the ICML Test-of-Time Award in 2011.  For the past ten years, McCallum has been active in research on statistical machine learning applied to text, especially information extraction, entity resolution, semi-supervised learning, topic models, word embeddings, and social network analysis.  His work on open peer review can be found at http://openreview.net.  Prof. McCallum's web page is http://www.cs.umass.edu/~mccallum.