About Me

I am a PhD student in Electrical Engineering at Stanford University, where I develop robust machine learning (ML) models for healthcare. At Stanford, I am lucky to be advised by Daniel Rubin and work with amazing collaborating PIs - Akshay Chaudhari, Christopher Lee-Messer, Jonathan Chen, and Wui Ip, check out my research page for details.

I am broadly interested in developing alternate sources of supervision for medical data such as observational supervision using passively-collected event logs and self-supervision strategies for data-efficient medical representation learning. The second pillar of my research is developing strategies for quantifying model trust and mitigating distribution shifts for reliable clinical deployment.

Since Spring 2020-21, I initiated and co-organize the Stanford MedAI Group Exchange Sessions, an inter-institutional weekly series featuring invited speakers discussing core AI/ML research in the context of medicine and healthcare. The talks are recorded/livestreamed and made publicly accessible on our YouTube channel.

Outside of research, I have several interests that span a wide gamut of things - including but not restricted to - travelling, social dance, gardening, music, art, creative writing, getting lost, hiking, biking and exploring new things.

Resume Academic CV

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