Tyler Simko

I am an Assistant Professor of Political Science at the University of Michigan. I specialize in US state and local politics, political geography, and computational social science.

I am a Co-PI of the Algorithm-Assisted Redistricting Methodology (ALARM) Project, a research group focused on how public policy influences spatial inequality. Before moving to Michigan, I was a Postdoctoral Research Associate at Princeton University in the Department of Politics. I received my PhD from the Department of Government at Harvard University in 2024. Before graduate school, I was elected to two terms on the South Amboy Board of Education in New Jersey and served as the President.

I have active research agendas in policy areas like electoral reform, legislative redistricting ("gerrymandering"), subnational policymaking by governments like city councils and school boards, administrative burdens, school segregation, and data privacy. Methodologically, I develop and use techniques in computational social science, causal inference, and machine learning to evaluate inequality and how it can be reduced. My work has been recognized with multiple awards from APSA and MPSA, including the Susan Clarke Young Scholar Award from the APSA Urban Politics Section. My work has also been covered by media outlets like The New York Times, The Washington Post, CBS News, and Associated Press.

As part of my work, I often create and publicly release large datasets using open-source tools. For example, I co-created LocalView — the largest audio, video, and text database of local government meetings in the United States — with Soubhik Barari. My work is motivated by real-world impact, and I regularly partner with federal, state, and local officials to improve program design and inform evidence-based policymaking.

I teach data science, artificial intelligence, and American politics courses at the graduate and undergraduate levels. For example, at Michigan I have recently taught courses on machine learning, LLMs, and non-tabular data (i.e. audio, video, spatial, etc.) for PhD students, and a course on contemporary challenges in local policymaking for undergraduates.

In other work, I am an Election Analyst for the CBS Data Desk. I am a former Data Scientist at the Office of Evaluation Sciences, where I worked in an interdisciplinary team to design causal evaluations of government programs.