Renjie Liao

Faculty Member

Assistant Professor, Department of Electrical and Computer Engineering, University of British Columbia

Canada CIFAR Artificial Intelligence Chair

Renjie Liao is an Assistant Professor at the Department of Electrical and Computer Engineering and an Associated Member of the Department of Computer Science at the University of British Columbia (UBC). He is a faculty member at the Vector Institute and a Canada CIFAR AI Chair. Before joining UBC, he was a Visiting Faculty Researcher at Google Brain, working with Geoffrey Hinton and David Fleet. He received his Ph.D. in CS in 2021 from the University of Toronto under the supervision of Richard Zemel and Raquel Urtasun. During his Ph.D., he worked as a Senior Research Scientist at Uber Advanced Technologies Group. He received an M.Phil. degree in CS in 2015 from the Chinese University of Hong Kong and a B.Eng. degree in Automation in 2011 from Beihang University. He is broadly interested in machine learning and its intersection with computer vision, self-driving, healthcare, and other areas, with a focus on probabilistic and geometric deep learning.

Research Interests

  • Deep Generative Models
  • Geometric Deep Learning
  • Probabilistic Inference
  • Computer Vision
  • Self-driving
  • AI for Healthcare

Highlights

  • Best paper award, International Workshop on Machine Learning in Medical Imaging, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023
  • Canada CIFAR AI Chair in 2023
  • Top Reviewer, ICML (2020) 
  • Best Reviewer, NeurIPS (2019) 
  • Best Paper Award, ICML Workshop on Tractable Probabilistic Modeling (2019)
  • RBC Graduate Fellowship, RBC (2019-2021)
  • Connaught International Scholarship for Doctoral Students, University of Toronto (2015-2019)

Publications

Systems and Methods for Latent Distribution Modeling for Scene-Consistent Motion Forecasting

Sergio Casas and Cole Chistian Gulino and Shun Da Suo and Katie Z Luo and Renjie Liao and Raquel Urtasun

2021

Systems and Methods for Jointly Performing Perception, Perception, and Motion Planning for an Autonomous System

Wenyuan Zeng and Shenlong Wang and Renjie Liao and Yun Chen and Bin Yang and Raquel Urtasun

2021

Systems and Methods for Autonomous Vehicle Systems Simulation

Raquel Urtasun and Kelvin Ka Wing Wong and Qiang Zhang and Bin Yang and Ming Liang and Renjie Liao

2021