StatMathAppli 2027

Yuting Wei is an Associate Professor in the Department of Statistics and Data Science at the Wharton School of the University of Pennsylvania, where she is also an affiliated faculty member in Applied Mathematics and Computational Science (AMCS). Her research lies at the intersection of mathematical statistics, machine learning, and information theory. She is particularly known for developing theoretical and algorithmic tools to interpret high-dimensional and structured data, alongside advancing the statistical foundations of reinforcement learning and diffusion models. 

Prior to joining the University of Pennsylvania, she was an Assistant Professor at Carnegie Mellon University and served as a Stein's Fellow and Lecturer at Stanford University. She earned her PhD in Statistics from the University of California, Berkeley, where she was associated with the Berkeley Artificial Intelligence Research (BAIR) group. She is a recipient of several prominent honors, including the 2026 Peter Gavin Hall IMS Early Career Prize, the 2025 ASA Gottfried E. Noether Early Career Scholar Award, a Google Research Scholar Award, and the NSF CAREER Award. She also received the Erich L. Lehmann Citation from UC Berkeley for an outstanding doctoral dissertation in theoretical statistics.

Jonathan Niles-Weed is an Associate Professor of Mathematics and Data Science at New York University's Courant Institute of Mathematical Sciences and the Center for Data Science, where he serves as the Director of Graduate Studies for the PhD Program. His research focuses on mathematical statistics, probability, and the mathematics of data science. He is particularly interested in the statistical and computational challenges of data with geometric structure, and much of his recent work centers on developing a statistical theory of optimal transport. He has recently co-authored a monograph on Statistical Optimal Transport. 

Prior to joining NYU, he earned his PhD in Mathematics and Statistics from the Massachusetts Institute of Technology (MIT) and was a Postdoctoral Member at the Institute for Advanced Study (IAS) in Princeton. He is a recipient of a Sloan Fellowship in Mathematics, an NSF CAREER award, the 2023 Tweedie New Researcher Award from the Institute for Mathematical Statistics, and the 2024 Early Career Prize from the SIAM Activity Group on Data Science.