Name: Kaushik Mohan
Email: kaushik.s.mohan@nyu.edu
Program: Statistics and Computational Social Science
Research Interests: Sequence Analysis, Statistical analysis of networks, Unsupervised Machine learning.
Principal Advisor(s): Ravi Shroff, Marc Scott
Research description/bio: Kaushik Mohan is a Ph.D student in the Statistics and Computational Social Science program at NYU. His research sits at the intersection of machine learning and social policy, where he develops tools to analyze the complexities of human trajectories, including career paths, life courses, and interactions with the criminal justice system. Originally trained in Engineering and Applied Mechanics at IIT Madras (B.Tech/M.Tech), it was his experience at a social start-up addressing urban poverty in Mumbai that sparked a shift toward the social impact space. This led him to NYU to pursue an M.S. in Applied Statistics for Social Science Research. Since then, he has been a part of the Data Science for Social Good Fellowship and continued to work in the Data for Good space, consulting for national and international non-profits across healthcare, transportation, and humanitarian development. He remains active in the civic tech community in NYC and is on the advisory board of a non-profit inspiring students to pursue a career in public interest technology. Outside his research, Kaushik is an aspiring crossword-setter who views a blank 15x15 grid as the ultimate optimization problem.
Selected Awards, Publications, and Presentations:
- Scott, M. A., Mohan, K., & Gauthier, J.-A. (2020). Model-based Clustering and Analysis of Life History Data. Journal of the Royal Statistical Society Series A: Statistics in Society, 183(3), 1231–1251.
- Mohan, K., Bergner, Y., & Halpin, P. (2020). Predicting Group Performance Using Process Data in a Collaborative Assessment. Technology, Knowledge and Learning, 25(2), 367–388.
- Investigating patterns of tourist movement using multiple data sources—Margarida Abreu Novais, Bruno Del Papa, Qiwei Han, Kaushik Mohan, Orsolya Vásárhelyi, Yanbing Wang, Leid Zejnilovic, 2025. (n.d.). Retrieved February 6, 2026.