Renjie Liao

Renjie Liao is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at The University of British Columbia. His research interests include Deep Learning, Machine Learning, Computer Vision, Self-Driving, Neural Language Models, Neural Symbolic Reasoning, and Statistical Learning Theory. Dr. Liao joined UBC in January 2022 and previously served as a Visiting Faculty Researcher at Google Brain. He holds a Ph.D. in Computer Science from the University of Toronto, an M.Phil. in Computer Science from the Chinese University of Hong Kong, and a B.Eng. in Automation from Beihang University. He welcomes applications from motivated students with a strong background in mathematics and/or coding, interested in his research areas.

Renjie Liao is a researcher at the University of British Columbia with expertise in Machine Learning, Computer Vision, Robotics, and Artificial Intelligence. His work focuses on advancing deep learning techniques for motion forecasting, video super-resolution, and semantic segmentation. He has developed innovative methods such as 3D graph neural networks for RGBD data and deep edge-aware filters for image processing. His research also explores graph-based approaches for relational behavior forecasting and scene-consistent motion prediction. Liao's contributions span across computer vision and robotics, with an emphasis on structured policies and perceptual similarity metrics in learning models.