I am an Assistant Professor in the Machine Learning Department at Carnegie Mellon University. I study the foundations of machine learning in social, policy, and healthcare settings, blending new methodology with field evaluations to improve AI’s societal impact. My work is shaped by collaborations with governments, nonprofits, health systems, and other partners. At CMU, I direct the Lab for AI and Social Impact. Our research has been funded by Schmidt Sciences, NSF, NIH, CDC, and the Engler Family Foundation. I completed my PhD in Computer Science at Harvard University. Before joining CMU, I was a postdoctoral Schmidt Science Fellow at the Harvard School of Public Health. I serve as Chair of the Board of Directors for EAAMO and the associated ACM EAAMO conference.

News

• July 2025: Paper on “Learning treatment effects while treating those in need” received the exemplary paper award for the AI track at EC 2025.
• February 2024: My dissertation received the honorable mention for the AAAI/ACM SIGAI Best Dissertation Award.
• September 2023: I will serve as co-PI of a CDC Center for Innovation at CMU.
• July 2023: Gave an invited tutorial at the International Conference on Stochastic Programming
• December 2022: Selected for a Schmidt Futures AI2050 Early Career Award
• August 2022: Invited talk at the KDD 2022 Workshop on Epidemiology meets Data Mining and Knowledge Discovery.
• July 2022: Invited talk in the CPAIOR Master Class on integrating machine learning and discrete optimization.
• January 2022: My dissertation received the IFAAMAS Victor Lesser Distinguished Dissertation Award.
• January 2021: Selected as one of 10 spotlight Rising Stars in Data Science by the University of Chicago.