I am currently a Research Assistant at Princeton University advised by Adji Bousso Dieng, working on theoretical machine learning, diversity measures, and sampling algorithms. I completed an integrated B.S. in Physics and M.S. in Mathematics from Indian Institute of Technology Kanpur, followed by an M.P.S. in Statistics and Data Science at Cornell University. My recent work includes a measure-theoretic generalization of the Vendi Score and Vendi-Dimensional Reduction. I am currently working on Vendi-regularized SVGD methods. In general, I am interested in research connecting spectral operator theory, probability, and optimization. I have also worked on random matrix theory, quantum algorithms, and constraint-aware deep learning for financial forecasting. Starting Fall 2026, I will join Georgia Institute of Technology as a Ph.D. student in ISyE under Dmitrii Ostrovskii. Long term, I am interested in industry research at the intersection of AI, optimization, and quantitative finance. Outside research, I enjoy soccer, hiking, and long mathematical discussions.

Fun fact: Although mathematics often feels like the language of certainty, I am equally fascinated by its limitations — Gödel’s incompleteness theorems remain one of my favorite reminders that even formal systems (math) cannot fully explain themselves.