Somjit Roy
Ph.D. in Statistics, Texas A&M University
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:
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Scientific machine learning for materials science and geosciences.
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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
| Sep 24, 2025 | Preprint on Bayesian SciML for Structural Learning of Scientific Expressions, arXiv:2509.19710 submitted. |
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| Sep 24, 2025 |
First official GitHub release of HierBOSSS on
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| Sep 27, 2025 | Invited talk on SPINWAVE at the minisymposium on Computational Methods for Multiscale and Multiphysics Problems at the 8th Annual SIAM Texas–Louisiana Workshop 2025 , Austin, TX. |
| Jul 27, 2025 |
First official GitHub release of TAVIE on
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| May 19, 2025 | Graduate Intern in the Earth and Environmental Sciences (EES) division at Los Alamos National Laboratory during the summer of 2025. |
| Apr 07, 2025 | Preprint on tangent-transform variational inference for strongly super-Gaussian likelihoods, arXiv:2504.05431. |
| 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, . |