Hello! I am a PhD student in the CILVR lab at NYU Courant working with Mengye Ren. My research is supported by the NDSEG fellowship. My research goal is to advance the visual perception and reasoning capabilities of AI agents to enable them to adeptly operate in real-world settings. I am currently exploring the following research directions:
Self-supervised learning on in-the-wild visual data
Learning representations and predictive models from video
Multimodal model architectures and training
Previously, I worked on the systematic equities research team at The Voleon Group as a machine learning engineer.
I completed my bachelor's and master's in computer science at the University of Michigan.
There, I was fortunate to work with Honglak Lee on reinforcement learning and representation learning, and Michael P. Wellman on multi-agent systems.
We propose a self-supervised learning framework that combines pooled and dense objectives to learn representations with spatial and semantic understanding from naturalistic videos.
We leverage successor features to formulate a graph-based planning framework and goal-conditioned policy, enabling long-horizon goal-reaching in visual environments.