Speaker: Xiao Luo, Ph.D. IDRE Fellow Department of Computer Science University of California Los Angeles   Time: 11:30 AM – 12:30 PM (PST) Date: March 28, 2024 Link to the recording: https://youtu.be/0_WwPe-kV-Q

Abstract: Many real-world systems such as disease transmission, molecular dynamics, and spring systems can be considered as multi-agent dynamical systems, where multiple objects interact with each other and exhibit complex behavior along the time. In this talk, I will discuss my current research on interacting dynamics system modeling for scientific problems, especially focusing on model construction and model generalization. I will begin by discussing my work on graph ODEs for efficiently capturing continuous high-order correlations. Then, I will discuss different types of distribution shifts in dynamical system modeling and how to address them to improve the generalization ability. Finally, I will introduce future research directions in the field of dynamical system modeling.

About the speaker: Dr. Xiao Luo is a postdoctoral researcher at UCLA’s Department of Computer Science. Previously, he received a B.S. degree in Mathematics from Nanjing University, Nanjing, China, in 2017 and a Ph.D. in the School of Mathematical Sciences from Peking University, Beijing, China in 2022. His research interests include machine learning on graphs, dynamical systems, statistical models, and AI for Science.