I’m a Computer Science PhD Student at UC, San Diego. My advisor is Sanjoy Dasgupta. I obtained my MS in Computer Science back in 2021 from UCSD. Before that, I graduated from UC Davis in 2019 with a BS in Mathematical and Scientific Computation and a BA in Philosophy with a minor in Computer Science.

Research areas: machine learning theory, weak supervision, unsupervised/semi-supervised learning

My research interests mostly involve ensemble methods – combining rules-of-thumb to create a classifier better than any specific part. Specifically, I’m interested in the setting where (i) the rules are weakly correlated with the ground truth (ii) there is no underlying generative process tying the rule predictions to the ground truth (iii) there is little to no labeled data. My focus is on adversarial methods and showing that they are viable from both theoretical and empirical viewpoints.