Brett J. Borghetti

Dr. Brett J. Borghetti is a Professor of Computer Science in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT), Graduate School of Engineering and Management, Wright-Patterson AFB, OH. He was promoted to Professor in July 2022, following prior appointments as Associate Professor (2017) and Assistant Professor (2008/2013). His expertise lies in artificial intelligence, machine learning, deep learning, cybersecurity, and human-machine teaming.

Education:

• Ph.D. in Computer Science, University of Minnesota, Twin Cities (2008)
• M.S. in Computer Systems, Air Force Institute of Technology (1996)
• B.S. in Electrical Engineering, Worcester Polytechnic Institute (1992)

Dr. Borghetti's research focuses on applying machine learning to physical science sensors (hyperspectral, seismic, RF), cybersecurity, and enhancing human-machine team performance. He teaches graduate courses in machine learning, AI, data security, and algorithm design, and advises numerous MS and PhD students in areas such as sensor exploitation, cognitive workload, and cyber situational awareness. His recent publications demonstrate strong trends in deep learning for multimodal sensor fusion, nuclear security, and neuroergonomics.

Scientific Awards:

• AETC Educator of the Year (2021, Civilian)
• AFIT Ezra Kotcher Teaching Award (2021)
• AFIT Teaching Excellence Award (2019)
• AF STEM Outstanding Science and Educator Award (2015)
• Multiple Eta Kappa Nu Outstanding Instructor Awards
• Air Force Meritorious Service Medal and other military honors

Dr. Borghetti has advised numerous graduate students and led research projects with significant funding and applications in defense and national security. He has directed research in AI-driven sensor analysis, cyber defense systems, and adaptive automation. His work often involves collaboration with national labs and DoD agencies. He has contributed to major research initiatives in human factors, cyber intruder detection, and machine learning for operational environments.

Labs and Research Teams: His work is associated with AFIT's research in cyber security, sensor exploitation, and human-machine systems. He collaborates with teams working on the Cyber Intruder Alert Testbed (CIAT), neuroergonomic modeling, and machine learning for defense applications.