About Me
Hi! I am a PhD student at Berkeley AI Research, advised by Alexei A. Efros (2023--).
I am interested in enhancing our scientific understanding of deep learning. Lately, I have been thinking about learning dynamics, universality in representations, properties of weight space, and the role of data.
My goal is to leverage these insights to guide the design of better algorithms and models. My research is supported by the DOE Computational Science Graduate Fellowship.
Previously, I graduated from Northwestern in 2023 with a BS in Computer Science. During my undergrad, I had the pleasure of working with many wonderful mentors: Pietro Perona,
Aggelos Katsaggelos, Jennifer J. Sun, Vibhav Vineet,
and Neel Joshi.
Recent News
[August 2025] Talks at: New England Mechanistic Interpretability Workshop, Cohere Labs, Northeastern, MIT.
[June 2025] New preprint released: "Vision Transformers Don't Need Trained Registers"
[June 2025] Co-organized the Mechanistic Interpretability for Vision Workshop at CVPR.
Selected Publications
(See my Google Scholar for a full list)
