Imon Banerjee

Imon Banerjee

Northwestern University: IEMS Alumni Fellow, Purdue University: PhD, Indian Statistical Institute: B.S. & M.S.

My current and ongoing projects

Ongoing Work

  1. Banerjee, I., Dutta, A., Bhattacharyya, R. (2026) A Retractive Perspective on Variational Inference.
  2. Gupta, V., Gurvich, I., Banerjee, I. (2026+) Optimal Control Problem for Particle Filters with Non-Gaussian Noise.
  3. Lei, J., Banerjee, I., & Mehrotra, S. (2026). A PCA formulation for Multi Change Point Detection on Regenerative Processes (Preprint on request).
  4. So, T., Banerjee, I., & Klabjan, D. (2026). Model Based Bootstrapping for the Transition Probabilities of Controlled Markov Chains Preprint.
  5. So, T., Banerjee, I., & Klabjan, D. (2026). Central Limit Theorems for Transition Probabilities of Controlled Markov Chains. Preprint
  6. Banerjee, I., Honnappa, H., & Rao, V. A. (2026). Adaptive Estimation of the Transition Densities of Controlled Markov Chains. Preprint
  7. Banerjee, I., Gurvich, I. (2026). Goggin’s Corrected Kalman Filter: Guarantees and Filtering Regimes. Major Revision at IEEE Transactions on Information Theory Preprint

Published Work

  1. Bhattacharyya, R., Chakraborty, S., Banerjee, I.. Adaptive Model Selection in Offline Contextual MDP’s without Stationarity. Transactions of Machine Learning Research, 2026. link
  2. Banerjee, I., & Honorio, J. Meta Sparse Principal Component Analysis. AISTATS, 2026. link
  3. Banerjee, I., Lei, J., & Mehrotra, S. Nonparametric Multi Change Point Detection for Markov Chains via Adaptive Clustering. AISTATS, 2026. link.
  4. Banerjee, I., Chakraborty, S. CLT and Edgeworth Expansion for m-out-of-n Bootstrap Estimators of The Studentized Median. NeurIPS, 2025. link
  5. Banerjee, I., Honnappa, H., & Rao, V. A.. Offline Estimation of Controlled Markov Chains: Minimaxity and Sample Complexity. Operations Research, 2025. link
  6. Banerjee, I., Rao, V. A., & Honnappa, H.. PAC-Bayes Bounds on Variational Tempered Posteriors for Markov Models. Approximate Bayesian Inference, Entropy, 2021. link
  7. Banerjee, I., Mullick, S. S., & Das, S.. On Convergence of the Class Membership Estimator in Fuzzy k-Nearest Neighbor Classifier. IEEE Transactions on Fuzzy Systems, 2019. link