I am an Assistant Professor of Mathematics and Data Science at NYU, affiliated with the Courant Institute and the Center for Data Science. Previously, I was a postdoctoral associate at MIT, hosted by Kaiming He. I received my Ph.D. in Computing and Mathematical Sciences from Caltech (2019–2025), where I was advised by Anima Anandkumar and Andrew Stuart. I received my B.S. from Washington University in St. Louis (2015–2019), majoring in computer science and mathematics with a minor in jazz. I am grateful to be supported by an AI2050 Early Career Fellowship.

My long-term goal is to develop machine learning methods for scientific computing and discovery. Specifically, I pioneer neural operators for learning solution operator in partial differential equations (PDEs) rising in fluid mechanics and earth science. Neural operators model physical simulation with chaotic behaviors and complex geometries, showing applications in weather forecasting, carbon storage, and aerodynamics simulation.

News: If you are interested in doing a PhD or postdoc with me, please do not hesitate to contact me!