Cassandra Handan-Nader is a Ph.D. candidate in Political Science with a Ph.D. minor in Computational and Mathematical Engineering. Her research develops and applies machine learning techniques to measure and characterize the structure of conflict in American political institutions. Before entering the Ph.D. program, she did freelance work as a data scientist in the energy, healthcare, and journalism sectors, followed by an empirical research fellowship at Stanford Law School, where she designed and analyzed policy evaluations for the administrative state. Her work with RegLab has been published in Nature Sustainability, American Economic Journal: Policy, Journal of Law, Economics, and Organization, and Stanford Law Review.