Sanjeev R. Kulkarni received the B.S. in Mathematics, B.S. in Electrical Engineering, M.S. in Mathematics from Clarkson University in 1983, 1984, and 1985, respectively, the M.S. degree in Electrical Engineering from Stanford University in 1985, and the Ph.D. in Electrical Engineering from M.I.T. in 1991.
Since 1991, he has been with Princeton University where he is currently Professor of Electrical Engineering and Dean of the Graduate School. He is also an affiliated faculty member of the Department of Operations Research and Financial Engineering and the Department of Philosophy. Prof. Kulkarni served as Director of the Keller Center from 2011-2014, Master of Butler College from 2004 to 2012, and Associate Dean for Academic Affairs in the School of Engineering and Applied Science from 2003-2005. He spent January 1996 as a research fellow at the Australian National University. He spent 1998 with Susquehanna International Group and was a regular consultant there from 1997 to 2001, working on statistical arbitrage and analysis of firm-wide stock trading. During Summer 2001, he was a visiting researcher at Flarion Technologies, Inc., working in the area of wireless communications. From 1985 to 1991 he was a Member of the Technical Staff at M.I.T. Lincoln Laboratory working on the modeling and processing of laser radar measurements.
Prof. Kulkarni received an ARO Young Investigator Award in 1992, and an NSF Young Investigator Award in 1994. He has also received several teaching awards at Princeton University, including the President's Award for Distinguished Teaching in May 2007, and seven awards from the Undergraduate Engineering Council for courses on computer vision, image processing, and signals and systems. Prof. Kulkarni is a Fellow of the IEEE, and he has served as an Associate Editor for the IEEE Transactions on Information Theory. Prof. Kulkarni's research interests include statistical pattern recognition, machine learning, nonparametric estimation, information theory, wireless networks, signal/image/video processing, and econometrics and finance.