About
I am a final-year PhD student in the Computer Science and Engineering (CSE) Division at the University of Michigan advised by Michał Dereziński. Prior to joining CSE, I completed a Master’s degree in Mathematics at the Indian Institute of Technology (IIT) Bombay, and worked in the banking industry for three years. I develop scalable machine learning algorithms for distributed and memory-constrained settings, with the goal of preserving statistical accuracy while reducing communication, computation, and memory costs. A central theme of my work is identifying model compression opportunities and designing distributed optimization methods that efficiently harness the compute capabilities of modern hardware accelerators. The theoretical foundations of my work lie in randomized numerical linear algebra, random matrix theory, and high-dimensional statistics.