Tom Goode is a data scientist at RAND and a professor of Public Policy at the RAND School of Public Policy. He leads quality, objective analyses to inform national security, homeland security, and public safety policymakers on topics including systems confrontation warfare, homeland defense strategy, defense and civilian critical infrastructure hardening, mass attack prevention, and the impact of AI developments on national and global security. Goode’s roles include serving as principal investigator for sponsors in the Office of the Secretary of War, coordinating large studies as a project manager, applying novel machine learning methods to complex data as a data scientist, and teaching statistical visualization to graduate students at the RAND School of Public Policy.
Outside of RAND, Goode supports the Military Operations Research Society as the junior analyst ambassador for its Data Science & AI community. He is also 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. Goode is the Director of Research Mentorship Program for the Journal of Collegiate EMS, where he facilitates mentor relationships between aspiring researchers and academic subject matter experts. He previously conducted research at the intersection of statistics, prehospital medicine, and emergency medical operations.
Goode holds an M.S. in statistical practice and a B.S. in statistics from Carnegie Mellon University.
M.S. in statistical practice, Carnegie Mellon University; B.S. in statistics, Carnegie Mellon University
