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My long-term goal is to build robots that continually use the knowledge gained during their lifespan to improve their performance and learn new tasks with human-like efficiency. As such, I work at the intersection of machine learning, robotics, and computer vision to develop intelligent robot systems with theoretically-founded lifelong learning capabilities. I am interested in a broad range of topics including Bayesian deep learning, conformal prediction, out-of-distribution detection and generalization, and continual learning. Recently, I have also been working on using Optimal Transport theory to solve machine learning problems.

I am currently an IVADO Postdoctoral Research Fellow at Mila-Quebec AI Institute. I am part of the Montreal Robotics and Embodied AI Lab (REAL) working with Professor Liam Paull.

Recent News

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.

Nov 1, 2021

I will be serving as a General Chair for the RSS Pioneers workshop 2022.

Jul 19, 2021

Our survey paper on probablistic object detection has been accepted to appear in the IEEE Transactions on Intelligent Transportation Systems. Code for surveyed methods is available here.

Jun 30, 2021

I began my new position as an  IVADO Postdoctoral Research Fellow at Mila-Quebec AI Institute.

Jun 17, 2021

I have successfully defended my Ph.D. thesis, which was accepted as is (no corrections required). Link to dissertation manuscript.

Jun 7, 2021

I have been selected to the Robotics Science and Systems pioneers cohort of 2021, a group of 30 leading senior PhD students and postdocs in the field. 

May 20, 2021

I have been acknowledged as an Outstanding Reviewer by CVPR 2021 organizers.

Mar 2, 2021

1 paper accepted to CVPR 2021 (Oral Presentation).

Jan 13, 2021

1 paper accepted to ICLR 2021.


Research Highlights

Contact Me


Phone: +1(519) 5040469