I am a Ph.D. Candidate in the ECE department at the University of Illinois Urbana-Champaign, where I am fortunate to be advised by Prof. R. Srikant. My research interests are in the theoretical foundations of machine learning, with a focus on stochastic optimization, generative models, and probability theory. My doctoral work centers on establishing asymptotically-tight finite-time performance characterizations of learning algorithms to better understand their fundamental limits.

I have had the opportunity to apply and expand my skills through several industry roles. During my internships at Amazon, I developed an ensemble model to predict customer satisfaction from sparse behavioral signals and built a listwise-ranking LLM as part of the search engine. Before my Ph.D., I spent three years as an AI Researcher and Team Lead at VUNO Inc., where I focused on building and leading the development of deep learning models for medical radiology.

I am a Ph.D. Candidate in the ECE department at the University of Illinois Urbana-Champaign, where I am fortunate to be advised by Prof. R. Srikant. My research interests are in the theoretical foundations of machine learning, with a focus on stochastic optimization, generative models, and probability theory. My doctoral work centers on establishing asymptotically-tight finite-time performance characterizations of learning algorithms to better understand their fundamental limits.

I have had the opportunity to apply and expand my skills through several industry roles. During my internships at Amazon, I developed an ensemble model to predict customer satisfaction from sparse behavioral signals and built a listwise-ranking LLM as part of the search engine. Before my Ph.D., I spent three years as an AI Researcher and Team Lead at VUNO Inc., where I focused on building and leading the development of deep learning models for medical radiology.