I am currently a Senior Research Scientist at Google Research.
My research explores the foundations of large-scale machine learning models. Recently, I have been working on improving text-to-image generation models with VLM-based feedback. I'm also interested in robustness and stability, including adversarial attacks and OOD generalization. Finally, I enjoy formulating new theoretical ML models, such as for sparsely activated mixture-of-experts networks, and new probing tasks for the equivariance of image embeddings.
Prior to Google, I was a postdoc at UCSD in the CSE department, working with Kamalika Chaudhuri, Sanjoy Dasgupta, and Paul Siegel. Before this, I was a visiting Research Scientist at Facebook Reality Labs, exploring Distributed Computing and Augmented Reality. In June 2018, I received my PhD in Computer Science & Engineering from the University of Washington (UW). My advisor was Paul Beame, and I was a part of both the Theory and MISL groups. I also spent time at Microsoft Research, working with the DNA Storage and the Theory groups. I obtained my BS from the Department of Computer Science at the University of Illinois Urbana-Champaign (UIUC).
(Dec 2023) Paper at NeurIPS 2023 on Benchmarking Robustness to Adversarial Image Obfuscations. Check out our dataset for a challenging new obfuscation-based robustness challenge!
(Nov 2023) Check out DreamSync our new approach to improve text-to-image generation models for both prompt alignment and visual aesthetics!