Soham Jana

Soham Jana is an Assistant Professor in the Department of Applied and Computational Mathematics and Statistics (ACMS) at the University of Notre Dame, part of the College of Science. He holds a Ph.D. in Statistics and Data Science from Yale University (2022), an M.Stat. and B.Stat. from the Indian Statistical Institute (ISI), Kolkata. His research focuses on high-dimensional statistics, robust estimation, statistical machine learning, causal inference, and empirical Bayes methods. Previously, he was a Post-doctoral Research Associate at Princeton University's Operations Research and Financial Engineering department.

Education:

• Ph.D., Yale University, 2022 (Thesis: Learning non-parametric and high-dimensional distributions via information-theoretic methods)
• M.Stat. (Hons.), Indian Statistical Institute, 2017 (Dissertation: Characterization of single-integral non-kernel divergences)
• B.Stat. (Hons.), Indian Statistical Institute, 2015

Research interests include theoretical and methodological aspects of high-dimensional statistics, robust estimation, neural networks, causal inference, and empirical Bayes. He has received awards such as the INSPIRE Scholarship and the Kaneb Center Course Design Academy Award (2024–2025, $5000).

Grants and professional contributions include organizing sessions at conferences like JSM and CFE-CMStatistics. His work spans collaborations with institutions like Princeton, Yale, and the First Republic Bank Research Program. He teaches courses such as Introduction to Probability and Modern Machine Learning Techniques at Notre Dame.