The goal of my research is to enable robots that can operate in unstructured, real-world environments. Towards this goal I study how robots can generalize effectively across tasks, objects, and environments by learning from large datasets. Specifically, my research focuses on methods for:

Scalably [1, 2] and safely [3] collecting real world robot datasets.
Self-supervised learning of visual models from offline data [1,2,3] and using them for robotic manipulation [4,5,6,7].
Leveraging human video datasets [1,3] and natural language annotations [2,3] to enable better robot learning.