Aaron Schein

I am an Assistant Professor in the Department of Statistics and the Data Science Institute at the University of Chicago. My research develops statistical and computational methodology for making sense of complex structured data in the social and biomedical sciences.

I am particularly motivated by data-intensive problems in political science as well as problems involving any combination of networks, time series, tensors, and high-dimensional discrete data. Much of my work takes a Bayesian or probabilistic perspective, and I enjoy developing models involving non-standard assumptions that are tailored to the data at hand. I also work on causal inference when real applied problems call for it. And more recently, like many others, I have started working on large language models, particularly on how they represent social scientific concepts.

I was previously a postdoctoral fellow in the Data Science Institute at Columbia University where I worked with David Blei and Donald Green on large-scale digital field experiments to assess the causal effects of friend-to-friend organizing on voter turnout in US elections. Prior to that, I did my PhD in Computer Science at UMass Amherst under the guidance of the one-and-only Hanna Wallach on Bayesian tensor models for discrete data of networks and time series in international relations. A fun fact about me is that I am officially tied for having the most degrees from UMass Amherst, where I also studied Linguistics and Political Science.