Tom is a data scientist at the RAND Corporation and a Professor of Public Policy at the Pardee RAND Graduate School. He leads quality, objective, quantitative analyses to inform national security, homeland security, and public safety policymakers on topics including military systems confrontation, disinformation, mass attack prevention, and the impact of AI developments on national and global security. Beyond wrangling complex datasets and applying novel statistical and machine learning methods, Tom has served as a project manager on large RAND studies and teaches statistical and machine learning methods at the Pardee RAND Graduate School.Beyond RAND, Tom is active in the field of prehospital emergency medicine and has received recognition both for academic contributions and for his literal fieldwork as an EMT and wilderness search and rescuer. He is the Director of Research Mentorship Program for the Journal of Collegiate EMS, where he facilitates mentor relationships between aspiring researchers and technical experts. Tom also supports the Military Operations Research Society as the junior analyst ambassador for its Data Science & AI community. He previously conducted research at the intersection of statistics, prehospital medicine, and emergency medical operations.Tom received his M.S. in Statistical Practice and B.S. in Statistics from Carnegie Mellon University.