Dr. Laura Freeman
Virginia Tech National Security Institute
Deputy Director
Deputy Director
UPCOMING EVENT
25th Annual Systems & Mission Engineering Conference
25th Annual Systems & Mission Engineering Conference
Bio
Dr. Laura Freeman is a Research Associate Professor of Statistics and dual hatted as the Deputy Director of the Virginia Tech National Security Institute and Assistant Dean for Research for the College of Science. Her research leverages experimental methods for conducting research that brings together cyber-physical systems, data science, artificial intelligence (AI), and machine learning to address critical challenges in national security. She develops new methods for test and evaluation focusing on emerging system technology. She focuses on transitioning emerging research to solve challenges in Defense and Homeland Security. She is also a hub faculty member in the Commonwealth Cyber Initiative and leads research in AI Assurance. As the Assistant Dean for Research for the College of Science, in that capacity she works to shape research directions and collaborations in across the College of Science in the Greater Washington D.C. area.Previously, Dr. Freeman was the Assistant Director of the Operational Evaluation Division at the Institute for Defense Analyses. In that position, she established and developed an interdisciplinary analytical team of statisticians, psychologists, and engineers to advance scientific approaches to DoD test and evaluation. During 2018, Dr. Freeman served as that acting Senior Technical Advisor for Director Operational Test and Evaluation (DOT&E). As the Senior Technical Advisor, Dr. Freeman provided leadership, advice, and counsel to all personnel on technical aspects of testing military systems. She reviewed test strategies, plans, and reports from all systems on DOT&E oversight.
Dr. Freeman has a B.S. in Aerospace Engineering, a M.S. in Statistics and a Ph.D. in Statistics, all from Virginia Tech. Her Ph.D. research was on design and analysis of experiments for reliability data.