Manish Raghavan

Manish Raghavan is the Drew Houston (2005) Career Development Professor at MIT Sloan School of Management (Information Technology group) and the Department of Electrical Engineering and Computer Science (EECS). He holds a PhD from Cornell University and a B.S. in EECS from UC Berkeley. His research focuses on applying computational techniques to societal challenges, including algorithmic fairness, online platforms, and behavioral economics. He co-authored foundational work on algorithmic fairness in hiring and testified before the EEOC on AI-driven employment discrimination.

Raghavan’s research interests span algorithmic fairness, AI ethics, and the societal impacts of automated decision-making. He has advised on AI policy for institutions like the Harvard CRCS and serves on Sai University’s International Advisory Board. His recent work examines generative AI’s impact on labor markets and hybrid intelligence frameworks for responsible AI use.

He advises students across EECS and IDSS, including postdocs Kate Donahue and Ziv Epstein. His awards include the ACM Doctoral Dissertation Award and Cornell’s CS PhD Dissertation Award. Current projects include seed grants for AI-augmented management and collaborations on census data privacy and algorithmic bias mitigation.