Ke Liمشاهده پروفایل
استادیار
- Machine Learning
- Computer Vision
- Algorithms
- +۴ مورد دیگر
Ke Li is an Assistant Professor at Simon Fraser University (SFU) in Vancouver, Canada. He previously worked at Google and the Institute for Advanced Study (IAS) in Princeton. He holds a Ph.D. from UC Berkeley, advised by Jitendra Malik, and a B.Sc. in Computer Science from the University of Toronto. His research focuses on machine learning, computer vision, and algorithms, with contributions to generative modeling, neural rendering, fast nearest neighbor search, and meta-learning. Education: Ph.D. in Computer Science, UC Berkeley (2016) B.Sc. in Computer Science, University of Toronto (2008) Research Interests: Dr. Li explores foundational challenges in machine learning, including: - Generative Modeling : Developing methods like Implicit Maximum Likelihood Estimation (IMLE) to improve generative model training. - Neural Rendering : Innovating techniques like Proximity Attention Point Rendering (PAPR) for dynamic 3D scene representation. - Fast Nearest Neighbor Search : Pioneering algorithms to overcome dimensionality curses. - Learning to Optimize : Automating algorithm design through reinforcement learning. Professional Activities: Organized the IAS Seminar Series on Theoretical Machine Learning with Sanjeev Arora Lead organizer of the BIRS Workshop on 3D Generative Models Reviewer for NeurIPS, ICML, CVPR, and other top conferences Teaching: Recently taught CMPT 726: Machine Learning and CMPT 983: Generative Models at SFU.









