I am a PhD student in the Theory
Group at UC Berkeley, advised by Jelani Nelson.
My research is broadly in algorithm design. I am particularly interested in algorithmic
questions arising from high-dimensional statistics, machine learning, and processing massive data.

I was a graduate student in the Theory of Computation group
at Harvard, before moving to Berkeley with my advisor.
Prior to that, I received my B.S. in Computer Science and in Mathematics from Duke
University, where I had the fortune of working with Rong Ge and Debmalya Panigrahi.

Publications

Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization

with Samuel B Hopkins and Jerry Li.

In Submission, 2020.

Optimal Robustness-Consistency Trade-offs for Learning-Augmented
Online Algorithms