Quanquan Gu
About
Quanquan Gu is an Associate Professor of Computer Science at the University of California, Los Angeles (UCLA) Samueli School of Engineering, where he conducts research in machine learning, data mining, and optimization algorithms with applications spanning deep learning, reinforcement learning, and computational genomics. He earned his Ph.D. in Computer Science from the University of Illinois at Urbana‑Champaign in 2014 and previously held faculty positions at the University of Virginia and postdoctoral research experience at Princeton University. Gu has received numerous awards for his work, including the NSF CAREER Award, Alfred P. Sloan Research Fellowship, AWS Machine Learning Research Award, and other honors that recognize his contributions to statistical machine learning and non‑convex optimization. His research aims to build the theoretical foundations of modern AI methods and apply them to complex data problems in science and engineering.
Research Performance Summary
First Recorded Paper
A similarity measure under Log-Euclidean metric for stereo matching
Year: 2008
Citations: 12
Venue: 2008 19th International Conference on Pattern Recognition
Latest Recorded Paper
Scalable Spatio-Temporal SE (3) Diffusion for Long-Horizon Protein Dynamics
Year: 2026
Citations: 0
Venue: arXiv preprint arXiv:2602.02128
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.