People
Zhouhan Chen
Contact: zc1245@nyu.edu
About: Zhouhan was a Ph.D. student at NYU Center for Data Science. His research lay at the intersection of social network analysis, cyber security, and machine learning. His focuses were on discovering and understanding the spread of misinformation across multiple platforms. Zhouhan was advised by Professor Richard Bonneau, Professor Juliana Freire, and Professor Joshua Tucker. Before coming to NYU, Zhouhan earned his Bachelor’s and Master’s degree in Computer Science at Rice University. Outside of school, Zhouhan is a longtime marathon runner and a certified personal trainer.
Leslie Huang
Contact: lesliehuang@nyu.edu
About: Leslie was a Ph.D. student in Data Science at the NYU Center for Data Science, where she was advised by Arthur Spirling. Her research was focused on NLP applications and text-as-data in political science. Leslie has a BA, summa cum laude, from Columbia University, and an MA from NYU, where she was a Ph.D. student in political science prior to joining Data Science.
Vladimir Kobzar
Vladimir was a PhD student at the NYU Center for Data Science where he was a part of the Math and Data Group. His graduate work was advised by Robert Kohn and Carlos Fernandez-Granda, and was supported in part by the Moore-Sloan Data Science Environment at New York University.
He completed an MS in Mathematics at the Courant Institute under the advisement of Afonso Bandeira, as well as a JD and LLM at the NYU School of Law.
His research area is mathematical and statistical foundations of data science and machine learning. I focus on their intersection with differential equations, control theory and optimization, and on applications to online learning, medical and molecular imaging, computer vision, robotics, finance and regulatory policy.
Wesley Maddox
Contact: wjm363@nyu.edu
About: Wesley was a Ph.D. student advised by Andrew Gordon Wilson. His interests were in statistical machine learning, bayesian deep learning, Gaussian processes, and generative models, with a specific focus on developing new methods to incorporate and utilize uncertainty in machine learning models. Prior to NYU, he spent two years as a Ph.D. student in Statistics at Cornell University and did a master’s in statistics and a bachelor’s degree in systems biology at Case Western Reserve University. In Summer 2019, he interned at Amazon in Cambridge, UK. He is an NSF Graduate Research Fellow, received in 2017.
Sreyas Mohan
About: Sreyas was a Ph.D. student at the Center for Data Science, NYU working under the joint guidance of Prof. Eero P Simoncelli and Prof. Carlos Fernandez-Granda. He was also a part of Math and Data Group. He graduated in July 2017 with a Bachelor’s in Electrical Engineering from the Indian Institute of Technology (IIT) Madras where his undergraduate thesis was supervised by Prof. Kaushik Mitra. Sreyas spent the summer of 2017 at the Institute of Science and Technology (IST), Austria working with Prof. Gasper Tkacik on deep learning models for a particular neuroscience application and the summer before that at the Simons Center for Data Analysis, NYC working with Dr. Dmitri Chklovskii in the intersection of unsupervised learning and computational neuroscience.