I am a Research Scientist at FAIR, Meta. The goal of my research is to enable robots with the ability to intelligently move (navigate) and do useful things (manipulate) in everyday environments (real world constraints).

These research goals manifest as challenges across the robotics stack ranging from perception to planning. To tackle them I often employ tools such as optimization and deep learning, and sensor modalities like vision and tactile. I also focus on developing 'structured' techniques that can leverage modern machine learning in a way that adds value over traditional robotics methods towards practical robot learning (data efficient, generalizable, interpretable).

Prior to joining FAIR, I received a Ph.D. in Robotics from Georgia Tech where I was advised by Byron Boots and was part of the Institute for Robotics and Intelligent Machines. During my Ph.D. I interned at NVIDIA Research, Amazon Robotics, and Honda Research Institute.