Biography
Ilya Davidson is a machine learning engineer and researcher whose work bridges computational methods and legal institutions. She is affiliated with CodeX, The Stanford Center for Legal Informatics, where she studies how data-driven approaches can reveal the hidden dynamics of judicial systems.
Ilya’s research applies natural language processing and network analysis to questions that have long resisted quantitative examination. Her current project examines federal judicial promotions in the United States using a longitudinal dataset spanning nearly a century—tracking over 360,000 district court cases and linking appellate outcomes through more than 90,000 circuit court decisions to the judges who authored the district opinions. By constructing citation networks, measuring judicial performance, and modeling promotion as a time-to-event process, the work reveals how political alignment, elite credentials, and judicial behavior interact to shape career advancement within the federal judiciary.
Before her work at CodeX, Ilya conducted research at the Risk-X institute in Shenzhen, China. Her academic background combines quantitative training with an interest in political and legal systems: she holds a Master’s degree in Econometrics and Data Analytics from the University of Amsterdam and a Bachelor’s degree in Econometrics from the University of Groningen. Previously she finished her first year of European Politics at King’s College London, where she developed an early interest in how political institutions function in practice.
