headshot of Taposh Banerjee

Taposh Banerjee

Assistant Professor
taposh.banerjee@pitt.edu
Website Industrial Engineering

overview

Dr. Taposh Banerjee is interested in developing theory and algorithms for sequential analysis, quickest change detection, stochastic optimal control, and machine learning. His research is inspired by concrete applications from cyber-physical systems, industrial engineering, neuroscience, and medicine. Issues that he has addressed through his research include energy efficiency, sampling control, nonstationary or periodic data, and multi-modal data. Before joining the University of Pittsburgh, he was an Assistant Professor of ECE at the University of Texas at San Antonio from 2018-2022. His work has been supported through grants from the National Science Foundation and the U.S. Army Research Laboratory. He received his Master of Engineering degree from the Indian Institute of Science Bangalore and his Ph.D. in ECE from the University of Illinois at Urbana-Champaign. He received his postdoctoral training from the University of Michigan, MIT, and Harvard University.

about

(2018 - 2022) Cloud Technology Endowed Professorship (UTSA).

(2016) Abraham Wald Prize in Sequential Analysis.

PhD, University of Illinois at Urbana-Champaign

ME, Indian Institute of Science Bangalore

Banerjee, T., & Tarokh, V. (2024). Bayesian quickest change detection for unnormalized and score-based models. Sequential Analysis, 43(3), 359-378.Informa UK Limited. doi: 10.1080/07474946.2024.2373118.

Banerjee, T., Gurram, P., & Whipps, G. (2024). Minimax asymptotically optimal quickest change detection for statistically periodic data. SIGNAL PROCESSING, 215, 109290.Elsevier. doi: 10.1016/j.sigpro.2023.109290.

Diao, E., Banerjee, T., & Tarokh, V. (2024). Large Deviation Analysis of Score-Based Hypothesis Testing. IEEE ACCESS, 12, 117691-117700.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/ACCESS.2024.3446848.

Hou, Y., Oleyaeimotlagh, Y., Mishra, R., Bidkhori, H., & Banerjee, T. (2024). Robust quickest change detection in nonstationary processes. Sequential Analysis, 43(3), 275-300.Informa UK Limited. doi: 10.1080/07474946.2024.2356555.

Wu, S., Diao, E., Banerjee, T., Ding, J., & Tarokh, V. (2024). Quickest Change Detection for Unnormalized Statistical Models. IEEE TRANSACTIONS ON INFORMATION THEORY, 70(2), 1220-1232.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TIT.2023.3328274.

Brucks, T., Banerjee, T., & Mishra, R. (2023). Modeling and quickest detection of a rapidly approaching object. SEQUENTIAL ANALYSIS-DESIGN METHODS AND APPLICATIONS, 42(4), 387-403.Taylor & Francis. doi: 10.1080/07474946.2023.2247020.

Oleyaeimotlagh, Y., Banerjee, T., Taha, A., & John, E. (2023). Quickest change detection in statistically periodic processes with unknown post-change distribution. SEQUENTIAL ANALYSIS-DESIGN METHODS AND APPLICATIONS, 42(4), 404-437.Taylor & Francis. doi: 10.1080/07474946.2023.2247035.

Nugroho, S.A., Vishnoi, S.C., Taha, A.F., Claudel, C.G., & Banerjee, T. (2022). Where Should Traffic Sensors Be Placed on Highways?. IEEE Transactions on Intelligent Transportation Systems, 23(8), 13026-13039.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tits.2021.3119211.

Banerjee, T., Gurram, P., & Whipps, G.T. (2021). A Bayesian Theory of Change Detection in Statistically Periodic Random Processes. IEEE Transactions on Information Theory, 67(4), 2562-2580.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tit.2021.3053149.

Angjelichinoski, M., Choi, J., Banerjee, T., Pesaran, B., & Tarokh, V. (2020). Cross-subject decoding of eye movement goals from local field potentials. Journal of Neural Engineering, 17(1), 016067.IOP Publishing. doi: 10.1088/1741-2552/ab6df3.

Angjelichinoski, M., Banerjee, T., Choi, J., Pesaran, B., & Tarokh, V. (2019). Minimax-optimal decoding of movement goals from local field potentials using complex spectral features. J Neural Eng, 16(4), 046001.IOP Publishing. doi: 10.1088/1741-2552/ab1a1f.

Banerjee, T., Firouzi, H., & Hero, A.O. (2018). Quickest Detection for Changes in Maximal kNN Coherence of Random Matrices. IEEE Transactions on Signal Processing, 66(17), 4490-4503.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tsp.2018.2855644.

Banerjee, T., & Moustakides, G.V. (2017). Minimax optimality of Shiryaev-Roberts procedure for quickest drift change detection of a Brownian motion. Sequential Analysis, 36(3), 355-369.Taylor & Francis. doi: 10.1080/07474946.2017.1360088.

Chen, Y.C., Banerjee, T., Dominguez-Garcia, A.D., & Veeravalli, V.V. (2016). Quickest Line Outage Detection and Identification. IEEE Transactions on Power Systems, 31(1), 749-758.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tpwrs.2015.2394246.

Banerjee, T., & Veeravalli, V.V. (2015). Data-Efficient Minimax Quickest Change Detection in a Decentralized System. Sequential Analysis, 34(2), 148-170.Taylor & Francis. doi: 10.1080/07474946.2015.1030971.

Banerjee, T., & Veeravalli, V.V. (2015). Data-Efficient Quickest Change Detection in Sensor Networks. IEEE Transactions on Signal Processing, 63(14), 3767-3775.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tsp.2015.2432737.

Banerjee, T., & Veeravalli, V.V. (2015). Data-Efficient Minimax Quickest Change Detection With Composite Post-Change Distribution. IEEE Transactions on Information Theory, 61(9), 5172-5184.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tit.2015.2458864.

Banerjee, T., & Veeravalli, V.V. (2014). Data-Efficient Quickest Change Detection. Sri Lankan Journal of Applied Statistics, 5(4), 183.Sri Lanka Journals Online (JOL). doi: 10.4038/sljastats.v5i4.7790.

Banerjee, T., & Veeravalli, V.V. (2013). Data-Efficient Quickest Change Detection in Minimax Settings. IEEE Transactions on Information Theory, 59(10), 6917-6931.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tit.2013.2272313.

Banerjee, T., & Veeravalli, V.V. (2012). Data-Efficient Quickest Change Detection with On–Off Observation Control. Sequential Analysis, 31(1), 40-77.Taylor & Francis. doi: 10.1080/07474946.2012.651981.

Banerjee, T., Sharma, V., Kavitha, V., & JayaPrakasam, A.K. (2011). Generalized Analysis of a Distributed Energy Efficient Algorithm for Change Detection. IEEE Transactions on Wireless Communications, 10(1), 91-101.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/twc.2010.110510.091177.

Chen, W., Banerjee, T., George, J., & Busart, C. (2023). Reinforcement Learning with an Abrupt Model Change. In Winter Simulation Conference.San Antonio.

Wu, S., Diao, E., Banerjee, T., Ding, J., & Tarokh, V. (2023). Score-based Change Point Detection for Unnormalized Models. In The 26th International Conference on Artificial Intelligence and Statistics (AISTATS).Palau de Congressos, Valencia, Spain.

Wu, S., Diao, E., Banerjee, T., Ding, J., & Tarokh, V. (2023). Robust Quickest Change Detection for Unnormalized Models. In 39th Conference on Uncertainty in Artificial Intelligence (UAI).Pittsburgh, PA.

Banerjee, T., Brucks, T., & Mishra, R. (2022). Quickest detection of a threat to an impending disaster. In 58th Annual Allerton Conference on Communication, Control, and Computing.Monticello.

Chen, W., Banerjee, T., & John, E. (2022). A Meta-Transfer Learning Approach to ECG Arrhythmia Detection. In Annu Int Conf IEEE Eng Med Biol Soc, 2022, (pp. 1300-1305).Institute of Electrical and Electronics Engineers (IEEE).United States. doi: 10.1109/EMBC48229.2022.9871518.

Banerjee, T., Padhy, S., Taha, A., & John, E. (2021). Quickest Joint Detection and Classification of Faults in Statistically Periodic Processes. In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 00, (pp. 5015-5019).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/icassp39728.2021.9414101.

Banerjee, T., Taha, A., & John, E. (2021). Robust Quickest Change Detection in Statistically Periodic Processes. In 2021 IEEE International Symposium on Information Theory (ISIT), 00, (pp. 101-105).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/isit45174.2021.9518067.

Banerjee, T., Gurram, P., & Whipps, G. (2020). Multislot and Multistream Quickest Change Detection in Statistically Periodic Processes. In 2020 IEEE International Symposium on Information Theory (ISIT), 00, (pp. 1147-1152).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/isit44484.2020.9174470.

Vishnoi, S.C., Nugroho, S.A., Taha, A.F., Claudel, C., & Banerjee, T. (2020). Asymmetric Cell Transmission Model-Based, Ramp-Connected Robust Traffic Density Estimation under Bounded Disturbances. In 2020 American Control Conference (ACC), 00, (pp. 1197-1202).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.23919/acc45564.2020.9147391.

Banerjee, T., Allsop, S., Tye, K.M., Ba, D., & Tarokh, V. (2019). Sequential Detection of Regime Changes in Neural Data. In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 00, (pp. 139-142).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/ner.2019.8716926.

Banerjee, T., Gurram, P., & Whipps, G. (2019). A Sequential Detection Theory for Statistically Periodic Random Processes. In 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 00, (pp. 290-297).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/allerton.2019.8919699.

Banerjee, T., Gurram, P., & Whipps, G. (2019). Bayesian Quickest Detection of Changes in Statistically Periodic Processes. In 2019 IEEE International Symposium on Information Theory (ISIT), 00, (pp. 2204-2208).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/isit.2019.8849824.

Banerjee, T., Gurram, P., & Whipps, G. (2019). QUICKEST DETECTION OF DEVIATIONS FROM PERIODIC STATISTICAL BEHAVIOR. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 00, (pp. 5351-5355).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/icassp.2019.8683006.

Banerjee, T., Choi, J., Pesaran, B., Ba, D., & Tarokh, V. (2018). Classification of Local Field Potentials using Gaussian Sequence Model. In 2018 IEEE Statistical Signal Processing Workshop (SSP), 00, (pp. 683-687).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/ssp.2018.8450778.

Banerjee, T., Choi, J., Pesaran, B., Ba, D., & Tarokh, V. (2018). Wavelet Shrinkage and Thresholding Based Robust Classification for Brain-Computer Interface. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 00, (pp. 836-840).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/icassp.2018.8462321.

Banerjee, T., Whipps, G., Gurram, P., & Tarokh, V. (2018). CYCLOSTATIONARY STATISTICAL MODELS AND ALGORITHMS FOR ANOMALY DETECTION USING MULTI-MODAL DATA. In 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 00, (pp. 126-130).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/globalsip.2018.8646417.

Banerjee, T., Whipps, G., Gurram, P., & Tarokh, V. (2018). Sequential Event Detection Using Multimodal Data in Nonstationary Environments. In 2018 21st International Conference on Information Fusion (FUSION), 00, (pp. 1940-1947).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.23919/icif.2018.8455835.

Banerjee, T., Liu, M., & How, J.P. (2017). Quickest Change Detection Approach to Optimal Control in Markov Decision Processes with Model Changes. In 2017 American Control Conference (ACC), (pp. 399-405).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.23919/acc.2017.7962986.

Banerjee, T., & Hero, A.O. (2016). Quickest Hub Discovery in Correlation Graphs. In 2016 50th Asilomar Conference on Signals, Systems and Computers, (pp. 1248-1255).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/acssc.2016.7869573.

Banerjee, T., Firouzi, H., & Hero, A.O. (2015). Non-Parametric Quickest Change Detection for Large Scale Random Matrices. In 2015 IEEE International Symposium on Information Theory (ISIT), (pp. 146-150).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/isit.2015.7282434.

Wu, S., Diao, E., Banerjee, T., Ding, J., & Tarokh, V. Score-based Change Point Detection for Unnormalized Models.