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 May 22, 2022

Taposh Banerjee

Taposh Banerjee

by utsaengineer / Thursday, 17 May 2018 / Published in
Cloud Technology Endowed Professorship IV, Assistant Professor
AET 2.362
210-458-5939
taposh.banerjee@utsa.edu
Personal website click here
 

Areas of Teaching Interest

Machine Learning, Digital Signal Processing, Probability and Stochastic Processes, Signal Detection and Estimation

Areas of Research Interest

Quickest Change Detection, Statistical Signal Processing, Machine Learning, High-Dimensional Statistics, Sequential Analysis, Time-Series Analysis, Reinforcement Learning, Optimal Stopping Theory, Biomedical Signal Processing.

Educational Background

Ph.D, University of Illinois at Urbana-Champaign, 2014.

Selected Publications

  • T. Banerjee, A. Taha, and E. John, “Robust Quickest Change Detection in Statistically Periodic Processes,” In Proc. of IEEE International Symposium on Information Theory (ISIT), Melbourne, Victoria, Australia, July 2021.
  • T. Banerjee, S. Padhy, A. Taha and E. John, “Quickest Joint Detection and Classification of Faults In Statistically Periodic Processes, In Proc. of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Toronto, Canada, June 2021.
  • T. Banerjee, P. Gurram and G. Whipps, “A Bayesian theory of change detection in statistically periodic random processes,” IEEE Transactions on Information Theory,  67(4), April 2021.
  • T. Banerjee, P. Gurram and G. Whipps, “Multislot and multistream quickest change detection in statistically periodic processes,” In Proc. of IEEE International Symposium on Information Theory (ISIT), Los Angeles, CA, June 2020.
  • T. Banerjee, E. Adib, A. Taha, and E. John, “Sequential methods for detecting a change in the distribution of an episodic process,” In Proc. of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020.
  • M. Angjelichinoski, J. Choi, T. Banerjee, B. Pesaran, and V. Tarokh, “Cross-subject decoding of eye movement goals from local field potentials”, Journal of Neural Engineering, 17(1), February 2020.
  • M. Angjelichinoski, T. Banerjee, J. Choi, B. Pesaran, and V. Tarokh, “Minimax-optimal decoding of movement goals from local field potentials using complex spectral features”, Journal of Neural Engineering, 16(4), May 2019.
  • T. Banerjee, P. Gurram and G. Whipps, “A Sequential Detection Theory for Statistically Periodic Random Processes,” In Proc. of 57th Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL, September 2019.  Invited. 
  • T. Banerjee, P. Gurram and G. Whipps, “Bayesian Quickest Detection of Changes in Statistically Periodic Processes,” In Proc. of IEEE International Symposium on Information Theory (ISIT), Paris, France, July 2019.
  • T. Banerjee, P. Gurram and G. Whipps, “Quickest Detection Of Deviations From Periodic Statistical Behavior,” In Proc. of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019.
  • T. Banerjee, S. Allsop, K. M. Tye, D. Ba, and V. Tarokh, “Sequential Detection of Regime Changes in Neural Data, ” In Proc. of 9th International IEEE EMBS Conference on Neural Engineering (NER), San Francisco, CA, March 2019.  
  • T. Banerjee, G. Whipps, P. Gurram, and V. Tarokh, “Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data,” In Proc. of IEEE Global Conference on Signal and Information Processing (GlobalSIP), Anaheim, CA, November 2018.
  • T. Banerjee, G. Whipps, P. Gurram, and V. Tarokh, “Sequential event detection using multimodal data in nonstationary environments,” In Proc. of International Conference on Information Fusion (FUSION), Cambridge, UK, July 2018.
  • T. Banerjee, J. Choi, B. Pesaran, D. Ba, and V. Tarokh, “Classification of local field potentials using Gaussian sequence model,” In Proc. of IEEE Statistical Signal Processing Workshop (SSP), Freiburg, Germany, June 2018.
  • T. Banerjee, J. Choi, B. Pesaran, D. Ba, and V. Tarokh, “Wavelet shrinkage and thresholding based robust classification for brain-computer interfaces,” In Proc. of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Alberta, Canada, April 2018.
  • T. Banerjee, H. Firouzi and A. O. Hero III, “Quickest detection for changes in maximal kNN coherence of random matrices,” IEEE Transactions on Signal Processing, 66(17): 4490 – 4503, September 2018.
  • T. Banerjee and G. Moustakides, “Minimax optimality of Shiryaev-Roberts procedure for quickest drift change detection of a Brownian motion,” Sequential Analysis, 36(3): 355 – 369, September, 2017.
  • T. Banerjee, Miao Liu and Jonathan P. How, “Quickest Change Detection Approach to Optimal Control in Markov Decision Processes with Model Changes,” In Proc. American Control Conference (ACC), Seattle, WA, May, 2017.
  • T. Banerjee and A. O. Hero III, “Quickest hub discovery in correlation graphs,” Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November, 2016. (Invited)
  • T. Banerjee and A. O. Hero III, “Quickest hub discovery in correlation graphs,” Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November, 2016. (Invited)
  • T. Banerjee and V. V Veeravalli, “Data-efficient minimax quickest change detection in a decentralized system,” Sequential Analysis, 34(2): 148-170, May, 2015. Winner of the Abraham Wald Prize in Sequential Analysis 2016
  • Y. C. Chen, T. Banerjee, A. D. Dominguez-Garcia, and V. V. Veeravalli, “Quickest line outage detection and identification,” IEEE Transactions on Power Systems, 31(1): 749 – 758, January, 2016.
  • 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.
  • 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.
  • T. Banerjee and V. V. Veeravalli, “Data-efficient quickest change detection,” Sri Lankan Journal of Applied Statistics, Special Issue: Modern Statistical Methodologies in the Cutting Edge of Science, with Guest Editor Professor Nitis Mukhopadhyay, pp. 183-208, 2014. (Invited)
  • 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.
  • 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.
  • T. Banerjee and V. V. Veeravalli, “Data-efficient quickest change detection with on-off observation control,” Sequential Analysis, 31(1): 40-77, February, 2012.
  • 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, 10(1): 91 -101, January, 2011.

 

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