I am a second year Ph.D. student at UC Berkeley, where I’m extremely fortunate to be coadvised by Prasad Raghavendra and Anant Sahai. I’m broadly interested in problems at the intersection of theoretical computer science and statistics, including topics such as computational complexity for inference problems, Markov chains, machine learning theory, and optimization. I graduated with a B.Sc. from MIT with a double major in mathematics (Course 18) and computer science (Course 6-3). I’m grateful to be supported by an NSF GRFP fellowship.
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear ModelsNeural Information Processing Systems, 2023
On the Training Instability of Shuffling SGD with Batch NormalizationInternational Conference on Machine Learning, 2023
Maximum A Posteriori Inference of Random Dot Product Graphs via Conic ProgrammingSIAM Journal on Optimization, 2022