Hi! I'm Samuel. I'm a computational social scientist who uses big data, applied math, and scientific computing to study large democratic elections.

I work at the Massachusetts Institute of Technology, as the Research Director of the MIT Election Data and Science Lab. I manage our voluminous election result data, and directed research for the 2022 Elections Performance Index and the Stanford-MIT Elections Performance Central. I have a PhD in Political Science and Scientific Computing and an MS in Math from the University of Michigan, and a BSc in Astrophysics from the University of Toronto.

I study problems in electoral democracy using novel empirical and computational methods. My core focus is the connection between comparative electoral institutions and voting behaviour: how do the rules of elections shape the way that people vote? I also develop computational methods for political science, and publish large empirical datasets. I've published work on voter strategy, election audits, measuring democracy, election administrators, and the potential consequences of novel electoral systems. I'm an Editorial Board Member of the Nature journal Scientific Data.

I'm also a computational activist and data-for-goodnik. I've written code to administer the internal elections of large non-governmental organizations, and have built datasets for use in elections for public office.


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  • Last modified
    2024-11-09