Carissma McGee

Carissma McGee is a graduate student in aeronautics and astronautics investigating whether commercial back-illuminated Sony CMOS detectors can approach the performance of expensive scientific CCDs and serve as accessible reference detectors for space telescopes. Her MATLAB pipelines, built with the Image Processing, Statistics and Machine Learning, and Curve Fitting Toolboxes, characterize the parameters dark current, read noise, per-pixel gain, and linearity while comprehensive total ionizing dose testing tracks how they degrade under radiation exposure. She also employs the Deep Learning Toolbox to develop neural networks that distinguish photon events from cosmic ray background across full image frames. As a second-year MathWorks Fellow, she aims to determine what commercial detectors can deliver on orbit, lowering barriers to flying capable imagers on CubeSats and satellite constellations while enabling commercial operators to achieve mission-grade sensing capability. By democratizing access to advanced imaging technology, her research has the potential to accelerate innovation across the commercial space industry and expand opportunities for organizations without substantial resources to develop custom space hardware.