Kyle Schindl

I am an assistant professor in the Department of Statistics at Iowa State University. In 2025 I completed my PhD in the Department of Statistics and Data Science at Carnegie Mellon University, where I was advised by Zach Branson, Edward H. Kennedy, and Joel Greenhouse. Before joining Carnegie Mellon, I received a Master of Science in Computational Analysis and Public Policy at the University of Chicago.

I am broadly interested in causal inference and experimental design. Much of my research centers around leveraging optimal transport theory to construct new causal inference tools. These causal tools are motivated by interdisciplinary collaborations in epidemiology, biostatistics, and economics.

My papers can be found below or on my Google Scholar page. Code for all of my research is publicly available via GitHub.

A copy of my C.V. can be found here.

Journal Publications