Zubin Jelveh

Zubin Jelveh is an Assistant Professor at the University of Maryland’s College of Information Studies (iSchool). He specializes in data science for public policy, record linkage, and the science of science. Prior to joining UMD in 2021, he served as a Research Director at Crime Lab New York, where he collaborated with civic leaders to design interventions targeting violence reduction and criminal justice reform.

Dr. Jelveh 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. His research bridges machine learning and social sciences, focusing on prediction models in criminal justice (e.g., domestic/gun violence) and record linkage algorithms tailored for justice data. He also examines scientific incentives and how research is presented.

His work emphasizes ethical AI applications, particularly in judicial systems, and includes projects like assessing pretrial risk in Maryland using CLUE data and targeting interventions for high-risk domestic violence victims. He explores themes such as algorithmic fairness, data quality in randomized experiments, and the impact of specialized prosecution strategies.

Before academia, Jelveh was a journalist covering economics for outlets like The New York Times. His interdisciplinary approach integrates computational methods with societal challenges, aiming to improve policy outcomes through rigorous data analysis.