About Me

Welcome! I am an Assistant Professor of the Practice in the Business Information & Analytics Department at the University of Denver’s Daniels College of Business. My research sits at the intersection of data science, public policy, and legislative institutions. I specialize in the use of computational methods to evaluate policymaking processes, particularly through the lens of evidence-based governance and legislative productivity.

My current research focuses on how artificial intelligence is reshaping policymaking at the local and federal levels, and how innovations in data transparency and civic monitoring - what scholars call monitory democracy - are transforming the relationship between governments and the public. Alongside conventional qualitative and quantitative methods, my research incorporates machine learning and large language models to analyze policy texts, legislative behavior, and transparency efforts.

Previously, I served as a Lead Data Scientist and Managing Consultant in public policy at ICF, where I led data science teams in the U.S. and the U.K., supporting public sector agencies on projects involving predictive analytics, automation, and policy evaluation. While in London, I was also a postdoctoral researcher in the Department of Politics at Birkbeck, University of London, where I contributed to a Leverhulme Trust-funded project on data innovation and monitory democracy in the Westminster Parliament.

I earned my PhD in Political Science from the University of Colorado Boulder, where my dissertation examined the conditions under which political actors’ preferences shape federal budget outcomes. I also hold degrees from the University of Texas at Austin (BA), the University of Nebraska Omaha (MS), and the University of Colorado Boulder (MA).