Zongyi Li

Zongyi is a Ph.D. student advised by Anima Anandkumar in the CMS department at Caltech (2019-2024). He has a broad interest in machine learning and applied math. Recently, Zongyi is focusing on developing deep learning methods for partial differential equations. He is leading the research on neural operator methods that generalize neural networks to operator learning settings. Zongyi received a B.S. with a double major in computer science and math at Washington University in St. Louis (2015-2019), when he was advised by Brendan Juba and Xiang Tang. He receives support from the Kortschak Scholarship, PIMCO Fellowship, Amazon AI4Science Fellowship, and NVIDIA Fellowship.