Taposh Banerjee

300 


Postdoctoral Fellow
John A. Paulson School of Engineering and Applied Sciences
Harvard University
33 Oxford Street
Cambridge, MA 02138

Google Scholar Link

ABOUT ME

I am a Postdoctoral Fellow at School of Engineering and Applied Sciences at Harvard University. I am working with Prof. Vahid Tarokh and Prof. Demba Ba.

My research interests lie in the areas of Statistical Signal Processing, Sequential Analysis, High-Dimensional Statistics, Statistical Learning, Reinforcement Learning, Decision Theory, and Stochastic Optimal Control.

I received my Ph.D. in ECE from the University of Illinois at Urbana-Champaign, where I worked in the Coordinated Science Laboratory. After graduation, I have been a postdoctoral associate/fellow at Massachusetts Institute of Technology (MIT) and the University of Michigan, Ann Arbor.

AWARDS

Abraham Wald Prize in Sequential Analysis 2016.

Recent Work:

  1. T. Banerjee, M. Liu and J. P. How, "Quickest Change Detection Approach to Optimal Control in Markov Decision Processes with Model Changes., Submitted, Sept. 2016.

  2. T. Banerjee and G. Moustakides, "Minimax Optimality of Shiryaev-Roberts Procedure for Quickest Drift Change Detection of a Brownian motion, Submitted, Oct. 2016.

  3. T. Banerjee, H. Firouzi and A. O. Hero III, “Quickest Detection for Changes in Maximal kNN Coherence of Random Matrices,” To be submitted.

  4. T. Banerjee and A. O. Hero III, “Quickest Hub Discovery in Correlation Graphs”, Asilomar 2016

Publications: Thesis/Book Chapter

  1. T. Banerjee, “Data-efficient quickest change detection,” Ph.D. Thesis, Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, August 2014.

  2. V. V. Veeravalli and T. Banerjee, “Quickest change detection,” Academic Press Library in Signal Processing: Volume 3 — Array and Statistical Signal Processing, pp. 209 - 255, 2014. arXiv copy

Publications: Data-Efficient Quickest Change Detection

  1. T. Banerjee and V. V. Veeravalli, “Data-efficient minimax quickest change detection with composite post-change distribution,” IEEE Transactions on Information Theory, 61(9): 5172 - 5184, September, 2015.

  2. T. Banerjee and V. V. Veeravalli, “Data-efficient minimax quickest change detection in a decentralized system,” Sequential Analysis, 34(2): 148-170, May, 2015.

  3. T. Banerjee and V. V. Veeravalli, “Data-efficient quickest change detection in minimax settings,” IEEE Transactions on Information Theory, 59(10): 6917 - 6931, October, 2013.

  4. T. Banerjee and V. V. Veeravalli, “Data-efficient quickest change detection with on-off observation control,” Sequential Analysis, vol. 31, no. 1, pp. 40-77, February, 2012.

Publications: Correlation Detection and Estimation

  1. T. Banerjee, H. Firouzi and A. O. Hero III, “Quickest Detection for Changes in Maximal kNN Coherence of Random Matrices,” To be submitted.

  2. T. Banerjee and A. O. Hero III, “Quickest Hub Discovery in Correlation Graphs”, Asilomar 2016

Publications: Decision Making in Nonstationary environments

  1. T. Banerjee, M. Liu and J. P. How, "Quickest Change Detection Approach to Optimal Control in Markov Decision Processes with Model Changes., Submitted, Sept. 2016.

Publications: Sensor Networks

  1. T. Banerjee and V. V. Veeravalli, “Data-efficient quickest change detection in sensor networks,” IEEE Transactions on Signal Processing, 63(14): 3727 - 3735, July, 2015.

  2. T. Banerjee and V. V. Veeravalli, “Energy-efficient quickest change detection in sensor networks,” In Proc. IEEE Statistical Signal Processing (SSP) Workshop, Ann Arbor, MI, August 2012. (This paper has two new algorithms not included in any of my journal papers on data-efficient quickest change detection)

  3. T. Banerjee, V. Sharma, V. Kavitha and A. K. JayaPrakasam, “Generalized analysis of a distributed energy-efficient algorithm for change detection,” IEEE Transactions on Wireless Communications, vol. 10, no. 1, pp. 91 -101, January, 2011.

  4. T. Banerjee and V. Sharma, “Generalized analysis of a distributed energy efficient algorithm for change detection,” In Proc. of ACM MSWiM, Canary Islands, Spain, 2009. (This paper has a delay computation technique not included in the journal version of the paper)