About me

Hi there! I’m a third-year PhD student in Computer Science at the University of Massachusetts Amherst, where I’m fortunate to be advised by Dr. Yair Zick. My research focuses on Trustworthy Reinforcement Learning (RL) and Machine Learning, with a particular emphasis on developing practical, fair, and robust algorithms.

My PhD journey has spanned a diverse range of topics, including model misspecification in RL, fairness in RL, fair resource allocation under uncertainty, and robust feature hightlighting. Beyond these core areas, I’ve delved into challenges in large language models (LLMs), such as investigating effects of fine-tuning on reasoning abilities, unlearning factual knowledge, and the robustness of alignment algorithms to noisy AI feedback.

I’ve also gained substantial industry experience as a research intern. At IBM Research (New York), I worked across three summers on projects including meta-hyperparameter tuning in RL, behavior policy search for efficient risk estimation, and glossary matching using LLMs, under the guidance of Dr. Dharmashankar Subramanian and Dr. Nhan Pham. More recently, I interned at Microsoft Research (India), where I explored the robustness of LLM alignment algorithms—a project currently in progress.

Before starting my PhD, I completed a Master’s degree in Computer Science at UMass Amherst in 2020, during which I had the privilege of working with external collaborators, Dr. Marek Petrik and Dr. Hima Lakkaraju. I also spent two years in industry as a Software Engineer at Flipkart and Endurance International Group. I graduated from NIT Durgapur with a B.Tech in Electronics and Communication Engineering.

When I’m not immersed in research, I enjoy reading, listening to science podcasts, and hiking.