Igor Gilitschenski

Igor Gilitschenski is an Assistant Professor in the Department of Computer Science at the University of Toronto. He leads the Toronto Intelligent Systems Lab, which focuses on embodied AI and robot learning. The lab's research spans robotics, computer vision, and machine learning, emphasizing foundation models, efficient scene representations, and novel perception modalities. Current interests include robotics, computer vision, and machine learning, with specific topics such as large-scale models for robotic perception, generative scene representations, and geometric deep learning.

Igor Gilitschenski is an Assistant Professor at the University of Toronto, specializing in Robotics, Machine Learning, and Computer Vision. His research focuses on developing advanced methodologies for autonomous systems, including visual-inertial mapping, perception, and control policies for autonomous driving. He has contributed to open-source frameworks like maplab and Vista 2.0, which support research in multimodal sensing and policy learning. His work also explores data-driven simulation, pedestrian intention estimation, and robust control strategies for dynamic environments. Gilitschenski's research emphasizes the integration of machine learning with robotics to enhance perception, navigation, and decision-making in complex scenarios.