Rohan Alur


I am a second year PhD student in the EECS department at MIT, where I'm fortunate to be advised by Manish Raghavan and Devavrat Shah. I am broadly interested in problems at the intersection of machine learning and economics, with a particular focus on causal inference, human/AI collaboration and policy learning. My work is supported by the Jae S. and Kyuho Lim Graduate Fellowship and a Stephen A. Schwarzman College of Computing seed grant. 

Prior to coming to MIT I worked for four years at Bridgewater Associates. I spent the latter half of my tenure there working closely with Jasjeet Sekhon as part Bridgewater's budding machine learning research group. Before that, I completed my B.S.E. in Networked and Social Systems Engineering ('NETS') and M.S.E. in Computer Science at The University of Pennsylvania. 

I am a volunteer mentor for the EECS Graduate Application Assistance Program (GAAP), which helps coach applicants through the PhD admissions process. If you are a prospective student I encourage you to check it out here.


Human Expertise in Algorithmic Prediction

RA, Manish Raghavan, Devavrat Shah


Auditing for Human Expertise 

RA, Loren Laine, Darrick K. Li, Manish Raghavan, Devavrat Shah, Dennis Shung 

Neural Information Processing Systems, 2023 | Spotlight Paper (top ~3% of submissions) 

Slides | Github | Blog Post

The Vascular Landscape of Human Cancer

Benjamin M Kahn, Alfredo Lucas*, RA*, Maximillian D Wengyn, Gregory W Schwartz, Jinyang Li, Kathryn Sun, H Carlo Maurer, Kenneth P Olive, Robert B Faryabi, Ben Z Stanger

Journal of Clinical Investigation, 2021