Bio
Maj McKay Williams is an Assistant Professor in the Department of Physics and Meteorology at the U.S. Air Force Academy, Colorado Springs, Colorado. He entered the Air Force in 2009 as a distinguished graduate of the Air Force Reserve Officer Training Corps, Detachment 860, Utah State University. He subsequently earned an M.S. in Electrical Engineering at the Air Force Institute of Technology and a Ph.D. in Imaging Science at the Rochester Institute of Technology. Maj Williams has balanced acquisition and academic assignments throughout his career, completing tours at Space Systems Command (SSC), the National Reconnaissance Office (NRO), and the Air Force Operational Test and Evaluation Center (AFOTEC). He ran live jamming & scintillation testing on strategic communication satellites, managed a $100M+/year electro-optical research & development portfolio, led a $4.3B+ spacecraft development contract, and served as Chief, Next Generation Overhead Persistent Infra-Red (OPIR) Payload Branch where his 42-member branch oversaw a $3.2B+ program to design, develop, integrate, and test all five mission payloads for the Next Generation OPIR Geosynchronous and Polar orbit programs. In 2021 he transferred to the U.S. Space Force.
Education
Air Command & Staff College, Maxwell Air Force Base, Alabama (2020)
Squadron Officer School, Maxwell Air Force Base, Alabama, residence (2018)
Doctor of Philosophy, Imaging Science, Rochester Institute of Technology, Rochester, New York (2017)
Spanish Language & Culture Scholar, Language Embedded Airman Program (2011-Present)
Master of Science, Electrical Engineering, Air Force Institute of Technology, Wright-Patterson AFB, Ohio (2011)
Bachelor of Science, Electrical Engineering, Utah State University, Logan, Utah (2009)
Professional Experience
Assistant Professor, Department of Physics, US Air Force Academy, Colorado (2023-Present)
Chief, Next Generation OPIR Payloads Branch, Space Sensing Directorate, Space Systems Command, Los Angeles AFB, California (2021-2023)
Chief, Space Vehicle Branch, Geospatial Intelligence Systems Acquisition Directorate, National Reconnaissance Office, Chantilly, Virginia (2020-2021)
Chief, Advanced Payloads Branch, Geospatial Intelligence Systems Acquisition Directorate, National Reconnaissance Office, Chantilly, Virginia (2019-2020)
Chief, Electro-Optic Tech & Advanced Optics Branch, Geospatial Intelligence Systems Acquisition Directorate, National Reconnaissance Office, Chantilly, Virginia (2017-2019)
PhD Student, Air Force Institute of Technology Civilian Institution Program, Rochester Institute of Technology, New York (2014-2017)
Lead Test Engineer, Air Force Operational Test and Evaluation Center (AFOTEC) Det 4, Peterson AFB, Colorado (2011-2014)
Master’s Student, Air Force Institute of Technology, Wright-Patterson AFB, Ohio (2009-2011)
Honors & Awards
Defense Meritorious Service Medal
Meritorious Service Medal
Air and Space Commendation Medal
Joint Service Achievement Medal
National Reconnaissance Office Field Grade Officer of the Year (2020)
Air Force Institute of Technology Louis F. Polk Award (2011)
Distinguished Graduate, Air Force Reserve Officer Training Corps (2009)
Research and Scholarly Interests
Electro-Optical/infra-Red Imaging Systems
Spacecraft Payloads
Remote Sensing & Image Processing
Communications & Signal Processing
Publications
Williams, McKay D. Generation, validation, and application of abundance map reference data for spectral unmixing. Rochester Institute of Technology, 2017.
Williams, McKay D., et al. “An introduction to abundance map reference data, with applications in spectral unmixing.” 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2017.
Williams, McKay D., John P. Kerekes, and Jan van Aardt. “Application of abundance map reference data for spectral unmixing.” Remote Sensing 9.8 (2017): 793.
Williams, McKay D., et al. “Validation of abundance map reference data for spectral unmixing.” Remote Sensing 9.5 (2017): 473.
Williams, McKay D., Jan van Aardt, and John P. Kerekes. “Generation of remotely sensed reference data using low altitude, high spatial resolution hyperspectral imagery.” Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII. Vol. 9840. SPIE, 2016.