Somjit Roy

Ph.D. in Statistics, Texas A&M University

Somjit Roy
At Oppenheimer's House

I am currently a doctoral candidate in Statistics at Texas A&M University, where I am advised by Dr. Bani K. Mallick (TAMU Statistics) and co-advised by Dr. Debdeep Pati (UW-Madison Statistics).

Research Interests

My research focuses on:

  • Scientific machine learning for materials science and geosciences.

  • Theoretical foundations and practical applications of Bayesian optimization and approximate Bayesian methods in multidisciplinary real-world problems.

For more insights into my work, visit the Research page.

News

Jul 27, 2025 First official GitHub release of TAVIE on .
May 19, 2025 Graduate Intern in the Earth and Environmental Sciences (EES) division at Los Alamos National Laboratory during the summer of 2025.
Apr 17, 2025 Work on (Bayesian) scientific machine learning for autonomous materials discovery, submitted.
Apr 07, 2025 Preprint on tangent-transform variational inference for strongly super-Gaussian likelihoods, .
Dec 28, 2024 Talk on TAVIE: Tangent Approximation for Variational Inference in different Exponential Families at IISA 2024.
Nov 19, 2024 Paper on Sparse Almost Perfect Mutually Unbiased Bases (APMUBs) got published in Journal of Statistical Theory and Practice, .