Jonathan Niles-Weed is an Associate Professor of Mathematics and Data Science at New York University. He studies mathematical statistics, the mathematics of data science, and applications of optimal transport in statistics, probability, and machine learning. He holds a PhD from the Massachusetts Institute of Technology and is the 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.