Research

Quickest Change Detection in Nonstationary or Periodically Stationary Data

1.  Y. Oleyaeimotlagh and T. Banerjee, "Modified Wald Formulation for Sequential Binary Hypothesis Testing in Statistically Periodic Processes," Accepted in Sequential Analysis, Oct 2025. 

2. Y. Hou, H. Bidkhori, and T Banerjee, "Robust Quickest Change Detection in Multi-Stream Non-Stationary Processes", IEEE Transactions on Information Theory, 71(11), November 2025.  

3. T. Banerjee, P. Gurram, and G. Whipps, "Minimax asymptotically optimal quickest change detection for statistically periodic data," Signal Processing (Elsevier), Volume 215, February 2024, 109290.

4. Y. Oleyaeimotlagh, T. Banerjee, A. Taha, and E. John, "Quickest change detection in statistically periodic processes with unknown post-change distribution", Sequential Analysis, 42(4), December 2023. 

5. T. Brucks, T. Banerjee, and R. Mishra, "Modeling and Quickest Detection of a Rapidly Approaching Object", Sequential Analysis, 42(4), December 2023. 

6. 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.

Quickest Change Detection in Unnormalized and Score-Based Models

1.  W. Chen, T. Banerjee, and V. Tarokh, "Conditional Score Learning for Quickest Change Detection in Markov Transition Kernels", Accepted with minor revisions in IEEE Transactions on Signal Processing, April 2026.

2. A. Adibi, S. Kulkarni, H. V. Poor, T. Banerjee, and V. Tarokh, "Asymptotically Optimal Change Detection for Unnormalized Pre- and Post-Change Distributions",  Accepted in Sequential Analysis, Oct 2025.  

3. S.  Moushegian, S. Wu, E. Diao, J. Ding, T. Banerjee, and V. Tarokh, "Robust Score-Based Quickest Change Detection", IEEE Transactions on Information Theory, 71(7), July 2025.   

4. T. Banerjee and V. Tarokh, "Bayesian Quickest Change Detection for Unnormalized and Score-Based Models,"  Sequential Analysis, 43 (3), August 2024.  

5. E. Diao, T. Banerjee, and V. Tarokh, "Large Deviation Analysis of Score-based Hypothesis Testing",  IEEE Access, 12, pp. 117691 - 117700, August 2024.

6. S. Wu, E. Diao, T. Banerjee, J. Ding, and V. Tarokh, "Quickest Change Detection for Unnormalized Statistical Models", IEEE Transactions on Information Theory, 70 (2),  February 2024. 

Quickest Change Detection with Sampling Control or Experiment Design

1. P. V. Lubenia and T. Banerjee, "Quickest change detection with cost-costrained experiment design", Under revision for IEEE Transactions on Information Theory, May 2026. https://arxiv.org/abs/2509.14186 .   

2. Y. Hou, H. Bidkhori, and T Banerjee, "Robust Quickest Change Detection with Sampling Control", IEEE Transactions on Signal Processing, vol. 73, pp. 3588-3597, 2025. 

3. 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.

4. 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.

5. 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

6. 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.

7. 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.

8. T. Banerjee and V. V. Veeravalli, "Data-efficient quickest change detection with on-off observation control," Sequential Analysis, 31(1): 40-77, February, 2012.

9. 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.

Quickest Correlation Change Detection

1. A. Alghamdi, T. Banerjee, and J. Rajgopal, "Robust Quickest Correlation Change Detection in High-Dimensional Random Vectors", Sequential Analysis, 44 (3), August 2025. 

2. 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. 

3. 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) 

Quickest Change Detection Applications: RL, Power Systems, Neuroscience, Cyber-Physical Systems 

1. T. Guo, T. Banerjee, R. Liu, and L. Su, "Building Real-time Awareness of Out-of-distribution in Trajectory Prediction for Autonomous Vehicles", Accepted in ACM Transactions on Cyber-Physical Systems, March 2026.

2. W. Chen, T. Banerjee, J. George, C. Busart, "Reinforcement Learning with an Abrupt Model Change", In Proc. of INFORMS Winter Simulation Conference (WSC), San Antonio, TX, December 2023. 

3. 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.  

4. 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. 

5. 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.

Machine Learning and Signal Processing for Medicine or Neuroscience

1. W. Chen, T. Banerjee, and E. John, "A Meta-Transfer Learning Approach to ECG Arrhythmia Detection", 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'22), Glasgow, United Kingdom, July 2022.

2. 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. 

3. 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. 

4. T. Banerjee, J. Choi, B. Pesaran, D. Ba, and V. Tarokh, "Classification of local field potentials using Gaussian sequence models," In Proc. of IEEE Statistical Signal Processing Workshop (SSP), Freiburg, Germany, June, 2018. 

5. 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. 

Quickest Change Detection with Multi-Modal Data

1. 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. 

2. 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.