4-192 Keller Hall (EE/CS Building), 200 Union Street SE,
Minneapolis, MN 55455
+1 (612) 625-0041 (office), (612) 625-0572 (fax)
Arindam Banerjee is an Assistant Professor and a McKnight Land Grant Professor in the Department of Computer Science & Engineering, and a Resident Fellow in the Institute on the Environment (IonE) at the University of Minnesota, Twin Cities. He received his Ph.D. from the University of Texas at Austin in 2005. His research interests are in Machine Learning and Data Mining, and their applications in complex real world problems including those in Text and Web Mining, Social Network Analysis, Climate and Environmental Sciences, Healthcare, Bioinformatics, and Finance.
Accenture Technology Labs,
161 N. Clark St, Chicago, IL 60601
Rayid Ghani is currently a senior researcher and leads the Analytics research group at Accenture Technology Labs. His recent work includes machine learning and data mining for business applications. He has worked on text mining algorithms specifically dealing with semi-supervised and active learning. Rayid has published several papers on these topics in machine learning and data mining conferences. He has co-organized several workshops at ICM and KDD including the ICML 2003 Workshop on “The Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining”, ICML 2005 workshop on Learning with Partially Classified Training Data, KDD 2003 workshop on Operational Text Classification, KDD 2006 and 2008 workshops on Data Mining for Business Applications which has recently lead to a book publication on Data Mining for Business Applications. In addition, Rayid has also been involved in organizing committees for several conferences including Area Chairs for CIKM and ECML and the KDD 2011 publicity chair.
Center for Computational Learning Systems,
Columbia University, 475 Riverside Drive, MC 7717 Suite 850, New York NY 10115
Claire Monteleoni is research faculty in the Center for Computational Learning Systems, and adjunct faculty in the Department of Computer Science, at Columbia University in the City of New York. Prior to joining Columbia, she was a postdoc in Computer Science and Engineering, at the University of California, San Diego. She completed her PhD in 2006 and her Masters in 2003, in Computer Science, at MIT. She did her undergraduate work, in Earth and Planetary Sciences, at Harvard University. Her research focus is on Machine Learning theory and algorithms, in particular: Learning from Data Streams, Clustering, Active Learning, and Privacy-Preserving Machine Learning. She has recently started working on Climate Informatics: accelerating discovery in Climate Science with Machine Learning. Her work in this area has received a Best Application Paper Award, and has been presented at an Expert Meeting of the Intergovernmental Panel on Climate Change (IPCC), a panel formed by the UN, that shared the 2007 Nobel Peace Prize.
IBM T.J. Watson Research Center,
Yorktown Heights, NY 10598
Vikas Sindhwani is a Research Staff Member in the Business Analytics and Mathematical Sciences Department at IBM Research, NY. He received a PhD in Computer Sciences in 2007 from the University of Chicago where his research focused on Semi-supervised kernel methods and Manifold Regularization. His recent research includes the design of large-scale machine learning systems, algorithms for learning with minimal supervision, and low-rank matrix approximations applied to Recommender Systems, Social media Analytics and Text modeling. He has several conference and journal publications in these areas, and has served on program committees and organizing committees for various machine learning conferences.