I am a rising 5th year PhD student at UC Berkeley, jointly advised by Jiantao Jiao and Kannan Ramchandran, affiliated with the BLISS and BAIR labs. I was previously an intern with Nevena Lazic and Dong Yin at Deepmind and with Ravishankar Krishnaswamy at MSR India.
I work on a variety of topics in the theory of machine learning with a general focus on the statistical and computational aspects of adaptive decision making problems and reinforcement learning. More recently, I have been interested in the application of these techniques in pushing our understanding of large language models. My research has largely focused on using mathematical frameworks to explain curious practical phenomena and ultimately provide intuitions missing in existing approaches.
In a previous life, I was a dual degree student at the Department of Electrical Engineering, IIT Madras. I am fortunate to have had Andrew Thangaraj as my thesis advisor and to have worked closely with Rahul Vaze.
April 2023: I taught a guest lecture for Statistical Machine Learning (ECE 6254) at Georgia Tech.
April 2023: I presented our work on pruning for matrix sensing at Georgia Tech.
January 2023: I presented our recent work on nonlinear bandits at Google Research India and MSR India.
November 2022: I will be at Neurips 2022. Hit me up if you will be around!
October 2022: I gave a talk on nonlinear bandits at the WNCG group at UT Austin.
Powered by Jekyll and Minimal Light theme.