Sanjeev R. Kulkarni

William R. Kenan Jr. Professor of Electrical Engineering and Operations Research and Financial Engineering
Office Phone
B310 Engineering Quadrangle
  • Ph.D., Massachusetts Institute of Technology, 1991
  • M.S., Electrical Engineering, Stanford University, 1985
  • M.S., Mathematics, Clarkson University, 1985
  • B.S., Electrical Engineering, Clarkson University, 1984
  • B.S., Mathematics, Clarkson University, 1983
William R. Kenan Jr. Professor of Electrical Engineering and Operations Research and Financial Engineering

My research spans a variety of areas including, statistical pattern recognition, machine learning; applied probability, nonparametric statistics; information theory, communications; wireless networks, sensor networks; signal, image, and video processing; adaptive systems, hybrid systems, control and econometrics and finance.

    Selected Publications
    1. M. Ozay, I. Esnaola, F.T. Yarman-Vural, S.R. Kulkarni, H.V. Poor, “Machine Learning Methods for Attack Detection in the Smart Grid,” IEEE Transactions on Neural Networks and Learning Systems, Vol. 27, No. 8, pp. 1773-1786, 2016.

    2. G. Harman, S.R. Kulkarni, H. Narayanan “sin(ωx) Can Approximate Almost Every Finite Set of Samples,” Constructive Approximation, Vol. 42, pp. 303-311, June, 2015.

    3. S. Shang, P. Cuff, P. Hui, S.R. Kulkarni “An Upper Bound on the Convergence Time for Quantized Consensus of Arbitrary Static Graphs,” IEEE Transactions on Automatic Control, Vol. 60, No. 4, pp. 1127-1132, April, 2015.

    4. A. Lozano, S.R. Kulkarni, R.E. Schapire, “Convergence and Consistency of Regularized Boosting With Weakly Dependent Observations,” IEEE Transactions on Information Theory, Vol. 60, No. 1, pp. 651-660, January 2014.

    5. J. Lunden, S.R. Kulkarni, V. Koivunen, H.V. Poor, “Multiagent reinforcement learning based spectrum sensing policies for cognitive radio networks,” IEEE Journal of Selected Topics in Signal Processing, Vol. 7, No. 5, pp. 858-868, October 2013.

    Google Scholar Profile

    Honors and Awards:

    • Phi Beta Kappa Teaching Award, Princeton University (2009)
    • President's Award for Distinguished Teaching, Princeton University (2007)
    • IEEE Fellow (2004)
    • SEAS Distinguished Teacher Award, School of Engineering and Applied Science, Princeton University (2004)
    • Walter Curtis Johnson Prize for Teaching Excellence in Electrical Engineering (2002)
    • NSF Young Investigator Award (NYI) (1994)
    • Emerson-Keyes Faculty Advancement Award from the School of Engineering and Applied Sciences, Princeton University (1994)
    Research Areas
    Data & Information Science