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Bio: I am a final year Ph.D. candidate in Computer Science at Stanford University advised by Stefano Ermon, where I’m affiliated with the SAIL and StatML groups. My research is centered around machine learning with limited labeled supervision, and is currently focused on developing techniques for better adaptation and controllability in deep generative models. I ground my methodological work in societal applications motivated by problems in sustainability and fairness.

My research is supported by the NSF GRFP, Stanford Graduate Fellowship, the Qualcomm Innovation Fellowship, and the Two Sigma Diversity PhD Fellowship. I completed my undergraduate studies in CS-Stats at Columbia, where I worked on problems in computational biology as part of the Pe’er lab.

I previously interned at Google Brain in 2019 as part of the Magenta project. In my free time I’m an avid tennis player, runner, and food enthusiast!