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.

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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)