Ashesh Rambachan

Ashesh Rambachan serves as Assistant Professor of Economics at the Massachusetts Institute of Technology (MIT), with a visiting appointment at Stanford University's Department of Economics and SIEPR for the 2025-2026 academic year. His primary institutional affiliation remains MIT's Department of Economics.

His research program integrates econometric theory with machine learning to advance causal inference methodologies, particularly in quasi-experimental designs and observational data analysis. Key focus areas include algorithmic fairness, structural model robustness, and the application of foundation models to economic problems. This interdisciplinary approach bridges theoretical econometrics with real-world policy evaluation challenges.

Analysis of his publication trajectory reveals increasing engagement with AI-driven methodologies since 2020, marked by a shift toward foundation models and large language models in economic contexts. His work consistently addresses credibility gaps in causal estimation while expanding into behavioral economics and algorithmic decision-making frameworks, reflecting evolving priorities in computational social science.

Scientific recognition includes:

• NeurIPS 2024 Spotlight Paper for "Evaluating the World Model Implicit in a Generative Model"

No explicit details regarding student advising, grant funding, or laboratory affiliations appear in current public records. His teaching portfolio includes MIT PhD courses on Algorithms and Behavioral Science (14.163) and Statistical Methods in Economics (14.380), alongside undergraduate instruction in Algorithmic and Human Decision-Making (S.6041).