I am a third year Ph.D. student in Computer Science at Stanford University advised by Stefano Ermon, where I'm affiliated with the SAIL and StatML groups. My research interests lie in probabilistic machine learning methods: in particular, I am interested in developing techniques for better adaptation in generative models, robust representation learning, and applications to compression.
My research is supported by the NSF GRFP, Stanford Graduate Fellowship, and the Qualcomm Innovation 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.
Fall 2019: Head Teaching Assistant for CS236: Deep Generative Models at Stanford
Fall 2018: Teaching Assistant for CS236: Deep Generative Models at Stanford
Spring 2017: Head Teaching Assistant for COMS4117: Machine Learning at Columbia
Reviewer: ICLR 2020, AAAI 2020, NeurIPS 2019, ICML 2019, ICLR 2019, R2L Workshop (NeurIPS 2018).
Workshop Co-Organizer: Information Theory & Machine Learning (NeurIPS 2019)