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Jonathan Niles-Weed is an Associate Professor at New York University with a focus on Mathematics and Data Science. He is a core member of the Mathematics Data Science and Statistical groups at the Courant Institute of Mathematical Sciences. His research primarily addresses statistical and computational problems that arise from the geometric structure of data. Recently, he has dedicated his work to developing the statistical theory of optimal transport. Jonathan received his Ph.D. in Mathematics and Statistics from the Massachusetts Institute of Technology under the supervision of Philippe Rigollet. His research has been supported by a number of prestigious organizations including the National Science Foundation, Google Research, and he was a fellow of the Alfred P. Sloan Foundation. He encourages interested individuals to apply to the graduate program in Data Science and Mathematics at NYU, mentioning his name in their applications. He has co-authored a monograph titled 'Statistical Optimal Transport.'
Open Program in Biomedical Sciences (Vilcek Institute) covers departments like Biochemistry, Pathology, Neuroscience, Microbiology, etc.