I am a Professional Specialist in the School of Public and International Affairs (SPIA) at Princeton University. I hold a Ph.D. and M.S. in criminology from the University of Pennsylvania and a B.S. in criminal justice from Sacramento State. My current work sits at the intersection of computational methods and public policy. I use large language models to automate the cleaning and processing of administrative police data at scale, and I am leading a project that applies a large-scale geospatial mobility dataset to measure how homelessness influences civilian behavior.

Much of my earlier research focuses on policing. I have studied whether officer demographics shape policing practices, evaluated methods for measuring racial discrimination, and examined how removing “bad apples” might influence complaints against officers. I have also conducted several studies on crime prevention through environmental design, including work on the effect of street-light outages on crime in Chicago.

A central part of my work is improving access to reliable crime and policing data so that researchers, practitioners, and the public can conduct more rigorous analyses, better understand the criminal justice system, including crime in their own communities, and make evidence-based decisions. To support this goal, I have cleaned and released comprehensive versions of major public safety datasets, including the full FBI Uniform Crime Reporting (UCR) Program data. I also develop open-source R packages and author instructional materials, including A Criminologist’s Guide to R: Crime by the Numbers. For non-technical users, I created the Crime Data Tool, an interactive platform that allows people to visualize trends in crime, arrests, police employment, and related measures across agencies and over time. Together, these resources make complex datasets more accessible, transparent, and usable for a broad range of audiences.