Assistant Professor. CS. Robotics. Machine Learning.
I am an Assistant Professor of Computer Science at University of Toronto and a Faculty Member at the Vector Institute. I direct the UofT People, AI and Robotics (PAIR) group. I am affiliated with Mechanical and Industrial Engineering (courtesy) and UofT Robotics Institute. I am also a Sr. Research Scientist at Nvidia.
I earned M.S. in Computer Science and Ph.D. in Operations Research from UC, Berkeley. I worked with Ken Goldberg at Berkeley AI Research (BAIR). I also worked closely with Pieter Abbeel, Alper Atamturk & UCSF Radiation Oncology. I was later a postdoc at Stanford AI Lab with Fei-Fei Li and Silvio Savarese.
My research vision is to build the Algorithmic Foundations for Generalizable Autonomy, that enables robots to acquire skills, at both cognitive & dexterous levels, and to seamlessly interact & collaborate with humans in novel environments. My group focuses on understanding structured inductive biases and causality for decision making. In particular we are looking at multi-modal object-centric and spatiotemporal event representations, self-supervised pre-training for reinforcement learning & control, principle of efficient dexterous skill learning.
I will be a Stephen Fleming Early Career Professor in Computer Science at Georgia Tech in Fall 2023. I will be in Interactive Computing affiliated with Robotics and Machine Learning programs.
Research Interests: Robotics, Reinforcement Learning & Optimal Control, Computer Vision
Current Applications: Mobile-Manipulation in Retail/Warehouse, personal, and surgical robotics. Read more at PAIR Website
Link to (reasonably recent) CV.
Contact me: Georgia Tech: firstname.lastname@example.org | UofT: email@example.com
I am accepting new students at all levels at Georgia Tech. Thanks for your interest in my group.
Please apply to either Computer Science, Robotics or Machine Learning Graduate Programs.
However, kindly do not contact me directly with regard to Graduate Application Evaluations. I do not make admissions decisions.
Please see the opportunities on lab website and contact me accordingly.
The following talks cover the progression of research over in my group since 2019.
Stanford University Robotics Seminar (October 2022)
MIT Deep Learning Seminar highlighting recent work (January 2020)
Topical Workshop Talks
Robot Learning with Implicit Representations: Perception, Action, and Simulation
RSS Workshop on Implicit Representations for Robotic Manipulation, (Jun 2022)
Paving the Path to Robot Autonomy with Simulation
ICRA Workshop on Releasing Robots into the Wild, (May 2022)
Structure in Reinforcement Learning for Robotics, Slides PDF
ICRA Workshop on Behavior Priors in RL, (May 2022)
Structured Inductive Bias for Imitation from Videos
CVPR Workshop on Learning from Instructional Videos, (Jun 2020).
Unsupervised Representations towards Counterfactual Predictions
CVPR Workshop on Compositionality in Computer Vision, (Jun 2020).
|Jan 21, 2023||2 papers at ICLR: Slotformer & SEA for Structured Exploration.|
|Jan 15, 2023||5 New Papers at ICRA 2023|
|Sep 15, 2022||2 papers at CoRL: RoboTube & Bayesian Obj Models.|
|Sep 12, 2022||3 papers at Neurips: MoCoda, Breaking Bad & SMPL.|
|Jul 8, 2022||New ECCV Paper on Differentiable Simulation for Grasping.|
|Jun 30, 2022||Workshop Talks at ICRA and RSS 2022|
|Jun 30, 2022||2 papers at IROS: Scalable Sim2Real & Mobile-Manip with Articulated Objects.|
|May 25, 2022||3 New RL papers: Koopman-RL @ICML, LFIW @L4DC, & GLIDE @WAFR|
|Mar 2, 2022||MAC, NSM and X-Pool accepted at CVPR 22.|
|Feb 28, 2022||New papers on planning(PlaTe) at ICRA 22 and RL (LFIW) at L4DC 22.|