Hello! I am a PhD student in the CILVR lab at NYU Courant advised by Mengye Ren and supported by the NDSEG fellowship.
My areas of interest are machine learning and computer vision.
My research goal is to advance the visual perception and reasoning capabilities of AI agents to enable them to robustly operate in the complex real world.
Towards this end, I am exploring the following directions:
Self-supervised learning methods for in-the-wild visual data
Learning discriminative representations and world models from videos
Multimodal model architectures and training algorithms
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.
