Jon Niles-Weed is an Assistant Professor of Mathematics and Data Science at the Courant Institute of Mathematical Sciences and the Center for Data Science at NYU, where he is a core member of the Math and Data group.
Jon studies statistics, probability, and the mathematics of data science. He is especially interested in statistical and computational problems arising from data with geometric structure, and his recent work focuses on optimal transport.
Jon received his PhD in Mathematics and Statistics from MIT, under the supervision of Philippe Rigollet.
- Computational Complexity of Statistical Inference, Fall 2021. Visiting Scientist.