Matt joined the plasma physics PhD program in Fall 2021. He received his bachelors degree in 2017 in Mechanical Engineering and Physics from Duke University, where he researched particle detector calibration using artificial neural networks, as well as alternative wind energy harvesting technologies. He then worked for two years as a Physics Modeling Engineer for General Motors before joining TAE Technologies as a Junior Scientist, focusing primarily on stability analysis and diagnostic hardware and software.
Advisor: Steve Sabbagh
Research Focus: Matt's current research focuses on disruption characterization, prediction, and avoidance for existing and future tokamak plasmas. He is also interested in alternative confinement concepts (namely the field-reversed configuration) for fusion plasmas, diagnostic development, and exploring data synthesis and analysis methods that leverage machine learning techniques.
M. Tobin et al, MHD mode identification by higher order singular value decomposition of C-2W Mirnov probe data. Review of Scientific Instruments 92, 043510 (2021); https://doi.org/10.1063/5.0043802
R.M. Magee et al, Experimental characterization of Alfvén modes in a field-reversed configuration plasma. Nuclear Fusion 58, 082011 (2018); https://doi.org/10.1088/1741-4326/aab6c6