I am a data scientist at the RAND Corporation in Pittsburgh, Pennsylvania. I use a variety of statistical and machine learning methods to provide policymakers with quality, objective analysis on a broad variety of homeland security and national security topics.

While earning my bachelor's and master's degrees in statistics at Carnegie Mellon University, I conducted research at the intersection of statistics, prehospital medicine, and emergency medical operations; this included work to improve forecasting methodology for ambulance demand in urban environments, visualize complex cardiac arrest treatment data, and explore the impact of continuing education on patient care. See my LinkedIn profile for a full list of my professional skills, certifications, and past experiences.

On the weekends, I work as an emergency medical technician on an ambulance at Munhall Area Prehospital Services in Homestead, Pennsylvania, and volunteer with the student-run Carnegie Mellon University Emergency Medical Service, where I served in numerous leadership roles as a student and currently chair the agency's Board of Advisors. Even when I'm not treating patients, escaping EMS is a challenge; I am the statistical reviewer for the Journal of Collegiate Emergency Medical Services, I advise current CMU students applying statistical methods to EMS data, and the majority of my independent research (which you can see here) relates to prehospital care or EMS operations.

In the evenings, I enjoy exploring the world of amateur radio (KC3NFW), losing online chess games, and creating craft cocktails with friends.