Machine Learning in Economics Summer Institute 2023 (MLESI23)

Announcing MLESI '23!

We are excited to welcome this year's cohort for the Machine Learning in Economics Summer Institute, which will be held in Chicago, August 16-23, 2023. Applications for the 2024 Institute will open in January. 

Program Description:

Every August, CAAI hosts the Machine Learning in Economics Summer Institute (MLESI), organized by Jens Ludwig, Sendhil Mullainathan, Ashesh Rambachan (MIT), and Jann Spiess (Stanford). Modeled after similar programs in behavioral economics, the Institute brings together leading researchers with advanced graduate students and junior faculty to build community and push forward cutting-edge research ideas. Past visiting faculty included Susan Athey, Guido Imbens, Annie Liang, Manish Raghavan, Stefan Wager, and many others bridging computer science, statistics, and economics.

This Year's Participating Faculty: 

This list is subject to change.

• Nikhil Agarwal, Professor of Economics, MIT
• Susan Athey, Professor of Economics of Technology, Stanford GSB
• Peter Bergman, Assc. Professor of Economics, UT-Austin
• Joshua Blumenstock, Associate Professpr, UC-Berkeley School of Information
• Will Dobbie, Professor of Public Policy, Harvard Kennedy School
• Peter Hull, Professor of Economics, Brown
• Danielle Li, Assc. Professor of Technological Innovation, Entrepreneurship, and Strategic Mgmt, MIT Sloan
• Annie Liang, Asst. Professor of Economics, Northwestern
• Andrew C. Miller, Research Scientist, Apple
• Sanjog Misra, Professor of Marketing, Chicago Booth
• Emma Pierson, Asst. Professor of Computer Science, Jacobs Technion-Cornell Institute
• Manish Raghavan, Asst. Professor of Informational Technology, MIT Sloan
• Vasilis Syrgkanis, Asst. Professor of Management Science and Engineering, Stanford
• Chenhao Tan, Asst. Professor of Computer Science, UChicago

Goal of the program:

1. to introduce researchers to the new methods and data used in machine learning (e.g., supervised and unsupervised learning algorithms, machine vision, text analysis), and how they relate to longstanding questions around causal inference, experimental design, fairness and bias, and econometric theory; and

2. to build intuitions for how these methods can open up new questions for economists in fields like macroeconomics, behavioral science, health, development, public, labor, or applied microeconomics generally.

Format:

MLESI23 will be held in-person on the University of Chicago campus in beautiful Hyde Park. The program typically includes lectures, panel discussions, tutorials, office hours, and social activities.

Eligibility:

Participation in the full program is by application, and limited to around 30 Ph.D. students and early-career researchers (post-docs and junior faculty who have completed their Ph.D. program in 2020 or later). Candidates in economics and related disciplines (e.g., computer science, statistics, etc.) who have a strong interest and advanced training in formal economics are welcome to apply. 

Application:

Applications are closed. Applications for the 2024 Institute will open in January.