Teresa Huang, Ph.D.

Teresa Huang is a research scientist at Google Research in New York City. She is broadly interested in geometric deep learning, theory and algorithms for foundation models, and machine learning for science. Before joining Google, she was a research fellow in the Flatiron Institute’s Center for Computational Mathematics. She completed her Ph.D. in 2024 at Johns Hopkins University, where she was co-advised by Professors Soledad Villar and Carey Priebe.