Zubin Jelveh’s research connects techniques from machine learning, particularly the area of natural language processing, to problems in the social sciences.

At Crime Lab New York, Zubin builds predictive models and evaluates their ability to improve outcomes above and beyond current practice. Additionally, he is developing record linkage algorithms that are tailored for the unique features of criminal justice data. 

He holds a BA in economics from the University of Chicago, an MA in quantitative methods in the social sciences from Columbia University, and a PhD in Computer Science from New York University.

In a previous life, Zubin was a journalist covering economics for outlets like The New York Times, Condé Nast Portfolio, and The New Republic.