Welcome!
About me
I am an Assistant Professor in the Department of Applied and Computational Mathematics and Statistics (ACMS) at the University of Notre Dame, IN, USA.
Education and past affiliations
Princeton University: Post-doctoral Researcher in ORFE, 2022 - 2024 (Advisors: Prof. Jianqing Fan and Prof. Sanjeev Kulkarni)
Yale University: Ph.D., Statistics and Data Science, 2017 - 2022 (Advisor: Prof. Yihong Wu)
Indian Statistical Institute, Kolkata: Master of Statistics (M.Stat), 2015 - 2017 (Advisor: Prof. Ayanendranath Basu)
Indian Statistical Institute, Kolkata: Bachelor of Statistics (B.Stat), 2012 - 2015
Research interests
Theoretical and methodological aspects of statistical machine learning, with particular focus on high-dimensional regimes, neural networks, mixture modeling, and distance-based estimators.
Recent papers
Chen, X., Jana, S., Metzler, C. A., Maleki, A., & Jalali, S. (2026). Multilook Coherent Imaging: Theoretical Guarantees and Algorithms. Accepted at IEEE Transactions on Information Theory. arXiv preprint arXiv:2505.23594. Paper link.
Jana, S. (2026). Minimax Theory of Likelihood-Based Deep Learning for Speckle Regression. arXiv preprint arXiv:2607.14064. Paper link.
Jana, S., Yang, K., & Kulkarni, S. (2026). Adversarially robust clustering with optimality guarantees. To appear at IEEE Transactions on Information Theory. DOI: 10.1109/TIT.2025.3628160. Paper link.
Xing, H., Jana, S., & Maleki, A. (2025). Minimax Analysis of Estimation Problems in Coherent Imaging. arXiv preprint arXiv:2508.18503. Paper link.
Jana, S., Polyanskiy, Y., & Wu, Y. (2025). Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods. Information and Inference: A Journal of the IMA, Volume 14, Issue 4, December 2025, iaaf027. Paper link.
Jana, S., Fan, J., & Kulkarni, S (2025). A Provable Initialization and Robust Clustering Method for General Mixture Models. IEEE Transactions on Information Theory, vol. 71, no. 9, pp. 7176-7207, Sept. 2025, doi: 10.1109/TIT.2025.3585804. Paper link.