Hello, I’m Mayee!

I am a PhD student in Computer Science at Stanford University, advised by Prof. Christopher Ré and part of the Hazy Research Lab.

I’m interested in exploring fundamental questions behind tools in modern machine learning and using them to develop new, theoretically grounded methods. My current interests revolve around how to encode and evaluate sources of supervision and side information throughout the ML pipeline (e.g. weakly/semi/self-supervised) through both information-theoretic and geometric lenses. In particular, my work in graduate school so far has applied this interest to latent variable graphical models, distribution shift, and representations learned via contrastive losses.

Previously, I graduated summa cum laude from Princeton University in 2019 with a concentration in Operations Research and Financial Engineering (ORFE) and a certificate in Applications of Computing. I worked on my senior thesis on quantum machine learning with Prof. Elad Hazan and completed junior independent work on modeling misinformation in social networks with Prof. Miklos Racz.

Publications and Preprints