Generate a tailored SOP for Dr. Jonathan Niles Weed. Improve your application with a focused, well-structured draft.
Jonathan Niles-Weed is an Associate Professor at the Courant Institute of Mathematical Sciences and a core member of the Mathematics Data Science groups at New York University (NYU). He specializes in the study of statistics, probability, and data science with a particular focus on statistical computational problems arising from geometric structures in data. His recent work is dedicated to developing a statistical theory for optimal transport. Jonathan received his Ph.D. in Mathematics and Statistics from the Massachusetts Institute of Technology (MIT), where he was supervised by Philippe Rigollet. His research has been supported by the National Science Foundation, Google Research, and the Alfred P. Sloan Foundation fellowship. He is dedicated to mentoring students who are applying to the graduate program in data science and mathematics at NYU, although he cannot respond to inquiries from admitted students. His collaborative work includes contributions from colleagues such as Sinho Chewi and Philippe Rigollet, and he is also the co-author of the monograph 'Statistical Optimal Transport.'
Open Program in Biomedical Sciences (Vilcek Institute) covers departments like Biochemistry, Pathology, Neuroscience, Microbiology, etc.