Stefani is a computational social science expert, with a background in political science, policy, and advanced quantitative methods. She uses supervised and unsupervised machine learning methods and data science best practices to generate insights for ICF’s government and commercial clients.
Stefani is expert in use of a variety of methodological techniques, including natural language processing and text analysis, experimental and survey methods, and advanced statistical modeling. She has published academic articles on use of a variety of quantitative methods on topics such as legislative policy capacity, the diffusion of environmental policy, and the influence of political indicators on state-level lawmaker behavior. Based in London, she is a senior member of ICF’s European data science team.
She has a PhD in Political Science from the University of Colorado Boulder.