My long-term research goal is to develop robust, lifelong learning robots that can perform effectively with uncertain and limited knowledge of the world, be easily deployed in new environments, and require minimal human intervention during their operation. As such, I work at the intersection of robotics, machine learning, and computer vision to develop robot learning systems that model and handle the uncertainty in their belief space while continuously learning new tasks from a few labeled examples.
Nov 23, 2021
I have recieved the 2021 G. N. Patterson Student Award, awarded to the most outstanding Ph.D. candidate to graduate from UTIAS during the year of 2021.
Mar 2, 2021
1 paper accepted to CVPR 2021 (Oral Presentation).
Jan 13, 2021
1 paper accepted to ICLR 2021.