Structural Deep Learning

Monday, May 13, 2024 - 4:00pm

Event Calendar Category

LIDS Seminar Series

Speaker Name

Sanjog Misra


University of Chicago

Building and Room Number



Humans have an amazing ability to describe the structure of the world in ways that allows for constraints, realisms and boundaries to be respected. This structure facilitates the notion of counterfactuals which is a fundamental element of any framework that aims at making decisions. In this talk, I will discuss the need for thinking of ML and in particular deep learning as embeddable objects in structural models of human (and group or firm) behavior. I will provide some relevant contexts, examples and applications of these ideas.


Sanjog Misra is the Charles H. Kellstadt Professor of Marketing & Applied AI at the University of Chicago Booth School of Business and the faculty co-director of the Center for Applied AI. His research focuses on the use of machine learning, deep learning and structural econometric methods to study consumer and firm decisions. In particular, his research involves building data-driven models aimed at understanding how consumers make choices and investigating firm decisions pertaining to pricing, targeting and salesforce management issues. More broadly, Professor Misra is interested in the development of scalable algorithms, calibrated on large-scale data, and the implementation of such algorithms in real world decision environments. Professor Misra's research has been published in the Econometrica, The Journal of Marketing Research, The Journal of Political Economy, Marketing Science, Quantitative Marketing and Economics, the Journal of Law and Economics, among others. He has served as the co-editor of Quantitative Marketing and Economics and as area editor at Management Science, the Journal of Business and Economic Statistics, Marketing Science, Quantitative Marketing and Economics, the International Journal of Research in Marketing and the Journal of Marketing Research.