Jonathan Power Email & Phone Number

Following my undergrad degree (B.S.E.E. from Cedarville University), I was hired as an entry level Electrical Engineer at the Sensors Directorate of the Air Force Research Laboratory (AFRL/RY) in 2013 via the Palace Acquire Program. In my three years of experience there, added a vast amount of skills and knowledge within the technical area of EO/IR Surveillance and Technologies. This included the following: assisting in flight data collections, deploying test targets, operating/testing Passive EO/IR sensors, organized lab testing of optical equipment and development/implementing algorithms for real time and post processing or imagery. During my AFRL tenure, I acquired a M.S.E.E. with a focus in Digital Image Processing from University of Dayton. As a result, I documented and developed thesis work in Atmospheric Turbulence Simulation for Long Range Passive Imagery that was utilized for AFRL projects.As part of my program, I moved to the Sensors Program Office within the Air Force Life Cycle Management Center (AFLCMC/WI) where I am currently stationed. While there, I have gained invaluable leadership and management skills alongside deep understanding and experience in the early Life Cycle areas of the Department of Defense's Acquisition Process. This has involved developing/reviewing acquisition documentation, leading/participating in efforts for addressing user capability gaps, providing technical insight for meeting program goals, establishing technical requirements/deliverables for programs, enabling cross-organizational collaboration teams for Multi-Intelligence system engineering projects, and coordinating with industry to inform technical development efforts and deliver needed capabilities to the Air Force. My main technical role during this timeframe has been as a GEOINT Subject Matter Expert for my team; this has deepened my technical knowledge and experience within the areas of Passive and Active EO/IR Sensing, Common Back-End Processor Standards, Artificial Intelligence/Machine Learning and Model Based System Engineering.