I am a PhD candidate at Stanford's Institute for Computational and Mathematical Engineering (ICME), advised by David Donoho and Andrea Montanari. I am interested in machine learning theory and statistical-computational tradeoffs in high dimensions. In summer 2026, I interned with Bruno Loureiro at ENS Paris. I earned an M.S. in Computational and Mathematical Engineering at Stanford, where I was a Vanguard Scholar in 2025–2026. I previously completed undergraduate degrees in Physics and in Mathematical and Computational Science with Honors at Stanford, where I was fortunate to work with Lexing Ying, Emma Brunskill, and Blas Cabrera. Between my undergraduate and graduate studies, I was a quantitative researcher at Goldman Sachs.
Recent Publications
arXiv preprint, 2026.
International Conference on Learning Representations (ICLR), 2025.
ICLR 2025 Workshops: Deep Generative Models in Machine Learning; Frontiers in Probabilistic Inference.
* Equal contribution.
A full list is available on my Google Scholar profile.
Teaching
Teaching Assistantships
- Math 131P – Partial Differential Equations (Winter 2026)
- Math 51 – Multivariable Calculus and Linear Algebra (Fall 2025)
- Physics 41E – Introductory Mechanics (Winter 2025)
Other Teaching and Mentoring
- Stanford Summer Academic Resource Center Tutor (Summer 2025)
- Stanford Code in Place (Spring 2024)
- Summer Science Program (SSP) Mentor (2021–present)