In collaboration with the Learning the Earth with Artificial Intelligence and Physics (LEAP), Dr. Li’s research at the Data Science Institute focuses on developing new algorithms for the use of sparse and indirect Earth observations that are organized across multiple space and time scales, in order to inform climate model parameterization. These data will refine initial parameterization based on machine learning approaches and informed by high-resolution high-fidelity simulations. Dr. Li will be employing various tools such as Bayesian inference, neural networks, and physical parameterizations with an initial focus on land, atmosphere or ocean. Furthermore, he will collaborate with scientists at the National Center for Atmospheric Research (NCAR) to refine and optimize parameterization processes.
Before joining Columbia University in July 2023, Dr. Li earned his Ph.D. in Fluid Dynamics and Hydrology and an M.S. in Computer Science from Duke University, where he was mentored by Professor Gabriel Katul.