Sanjeev R. Kulkarni

Sanjeev R. Kulkarni is the William R. Kenan Jr. Professor of Electrical and Computer Engineering and Operations Research and Financial Engineering at Princeton University's Department of Electrical Engineering. His research focuses on Data & Information Science, encompassing areas such as statistical pattern recognition, machine learning, applied probability, nonparametric statistics, information theory, communications, wireless networks, sensor networks, signal processing, and adaptive systems. He has contributed to various publications and has received multiple teaching awards at Princeton University, including the Phi Beta Kappa Teaching Award and the President's Award for Distinguished Teaching.

Sanjeev Kulkarni is a Professor of Electrical and Computer Engineering at Princeton University, specializing in statistical pattern recognition, machine learning, information theory, and signal processing. His research focuses on developing advanced methodologies for attack detection in smart grids, distributed learning in wireless sensor networks, and divergence estimation for multidimensional densities. He has also explored applications in cyber threat hunting, federated learning, and video annotation. His work emphasizes the intersection of theoretical foundations and practical implementations, contributing to areas such as signal processing, information theory, and machine learning. Kulkarni's research addresses challenges in wireless networks, power systems, and data-driven decision-making.