I am a Professional Specialist at the School of Public and International Affairs (SPIA) at Princeton University. I hold a Ph.D. and an M.S. in criminology from the University of Pennsylvania and a B.S. in criminal justice from Sacramento State. My current work combines computational methods and public policy by using large language models to automate the cleaning and processing of administrative police data to be analyzed. I am also working on a project that leverages a large-scale mobility dataset to measure how homelessness influences voting behavior.

Much of my earlier work lies in the field of policing. I have studied if officer demographics influences policing practices, worked to improve methods for measuring racial discrimination, and explored whether removing “bad apples” would affect complaints against the police. Additionally, I have conducted several studies on crime prevention through environmental design, including examining the effect of street light outages on crime in Chicago.

In support of my research and broader efforts to improve data accessibility, I primarily use the R programming language. I have developed several R packages and authored a book on R, “A Criminologist’s Guide to R: Crime by the Numbers,” published by CRC Press. To help non-technical users explore crime (and other) data, I created the Crime Data Tool, an interactive platform that enables users to visualize and analyze trends in crime, arrests, officer employment, and related areas across various agencies and time-frames. I have also cleaned and released versions of the full FBI Uniform Crime Reporting (UCR) Program data on the Harvard Dataverse to support transparency and reproducibility. These data are available here.