CUSP Research Seminar: Physics-Guided AI for Learning Spatiotemporal Dynamics

Lecture / Panel
Open to the Public


Please join NYU CUSP for our Research Seminar Series, featuring leading voices in the growing field of Urban Informatics. Our next virtual seminar will feature Rose Yu, Assistant Professor, University of California San Diego, for a discussion on “Physics-Guided AI for Learning Spatiotemporal Dynamics.”

Zoom link provided with RSVP

CUSP’s research seminars are open to the public!

Physics-Guided AI for Learning Spatiotemporal Dynamics

Abstract: Applications such as public health, transportation, climate science, and aerospace engineering require learning complex dynamics from large-scale spatiotemporal data. Such data is often non-linear, non-Euclidean, high-dimensional, and demonstrates complicated dependencies. Existing machine learning frameworks are still insufficient to learn spatiotemporal dynamics as they often fail to exploit the underlying physics principles. I will demonstrate how to inject physical knowledge in AI to deal with these challenges. I will showcase the application of these methods to problems such as forecasting COVID-19, traffic modeling, accelerating turbulence simulations, and combating ground effect in quadcopter landing.

Dr. Rose Yu is an assistant professor at the University of California San Diego, Department of Computer Science and Engineering. She earned her Ph.D. in Computer Sciences at the University of Southern California in 2017. She was subsequently a Postdoctoral Fellow at the California Institute of Technology. She was an assistant professor at Northeastern University prior to her appointment at UCSD. Her research focuses on advancing machine learning techniques for large-scale spatiotemporal data analysis, with applications to sustainability, health, and physical sciences. A particular emphasis of her research is on physics-guided AI which aims to integrate first-principles with data-driven models. Among her awards, she has won Google Faculty Research Award, Adobe Data Science Research Award, NSF CRII Award, Best Dissertation Award in USC, and was nominated as one of the ’MIT Rising Stars in EECS’.