Machine Learning in Economics Summer Conference (MLESC24)

Announcing MLESC '24!

We are excited to welcome this year's presenter's for the Machine Learning in Economics Summer Conference, which will be held in Chicago, August 6-7, 2024. Submit your paper for the 2024 Conference here.

Program Description:

Sanjog Misra of the University of Chicago Booth School of Business, Sendhil Mullainathan of the University of Chicago Booth School of Business, Annie Liang of Northwestern University, Jann Spiess of Stanford University, and Ashesh Rambachan of Massachusetts Institute of Technology are organizing the first Machine Learning in Economics Summer Conference (MLESC). 

The MLESC conference brings together researchers working at the intersection of machine learning and economics. It will focus on research studying how machine learning methods (e.g., supervised and unsupervised learning algorithms, machine vision, text analysis) may be used to tackle existing questions and open new directions in fields like behavioral economics, applied microeconomics, development, and macroeconomics. Both empirical and theoretical papers are welcome. 

Application:

The MLESC conference will be held at the University of Chicago on August 6–7, 2024. 


Please submit papers here. Submission of full drafts is encouraged, but extended abstracts of manuscripts that will be available by the time of the conference are possible. The submission deadline is April 12th, 2024. Please contact Lauren Doan if you have any questions. 


The conference will take place after this year’s Machine Learning in Economics Summer Institute, which will be held on August 1–5 and consist of workshops and tutorials for graduate students.

Graduate students admitted to MLESI will be in attendance at the conference.
Graduate students interested in applying for MLESI can find application materials here.

Conference Organizers

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