Welcome to the Toronto Intelligent Systems Lab

Our lab is a place for computer scientists and creative thinkers to come together and design the next generation of algorithms for robotic intelligence. The lab is located at the University of Toronto and led by Igor Gilitschenski.

Welcome to the Toronto Intelligent Systems Lab

Research Agenda

Our goal is to enabke Embodied AI and robot learning inspired by the human learning process. The current work focuses on foundation models for building efficient scene representations and simulation environments as well as robot learning in these environments. We are also interested in novel perception and sensing modalities. Overall, our research spans basic problems in machine learning, computer vision, and robotics. Current interests involve the following topics:

  • Robotics: Large-scale Models for Robotic Perception and robust Policy Learning.
  • Computer Vision: Efficient & Editable Neural 3D Reconstruction, Generative Scene Representations, Neuromorphic Vision.
  • Machine Learning: Geometric Deep Learning, Causal Representation Learning, Reinforcement Learning, Imitation Learning.