Edward Raff leads the Booz Allen machine-learning (ML) research team. In this role, he develops high-end technical talent and disseminates the latest skills, techniques, and knowledge across the firm. By collaborating with our research-oriented clients to address complex problems that can’t be solved with off-the-shelf techniques, he manages, guides, and implements advanced research into practice.
Edward is a noted expert in ML for malware detection. He has also published research and supported clients in applications related to health, adversarial machine learning attacks and defenses, reproducibility in ML, biometrics, and ethics. To his Booz Allen work, he brings a special focus on algorithm or software design changes that can scale up training to address ever-larger problems.
Prior to joining Booz Allen, Edward gained in-depth industry experience through projects with State Farm, Qualcomm, Microsoft, and Texas Instruments to design tools and tests that were still in use more than a decade later.
Edward chairs the Conference on Applied Machine Learning for Information Security and co-chairs the Artificial Intelligence for Cyber Security Workshop. He is a visiting professor at the University of Maryland, Baltimore County. He is a member of the Association for the Advancement of Artificial Intelligence, Association of Computing Machinery, and Institute of Electrical and Electronics Engineers. He also maintains the Java Statistical Analysis Tool library for ML.
Edward completed his Ph.D. in computer science at the University of Maryland, Baltimore County. He holds a B.S. and an M.S. in computer science from Purdue University.
