I am a PhD student in Applied Mathematics at Harvard, where I am supervised by Professor Cengiz Pehlevan. My work focuses on the mathematics of machine learning.

During my PhD, I’m interested in describing neural computation in the context of structured data and tasks, using tools from statistical physics and geometry. My current projects focus on exact analysis of in-context learning using random matrix theory, and the effects of low-dimensional structure on learning dynamics. My past research spans a range of applied maths areas, including early-universe cosmology, group theory, and ML4Physics.

I’m always happy to discuss my work and related topics, please reach out!