D.A. Humphreys

Papers

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About

D.A. Humphreys is a leading figure in fusion energy research, with a focus on integrating machine learning and artificial intelligence to accelerate progress in magnetic confinement fusion. His major contributions center on advancing the application of ML/AI methods to solve critical challenges in plasma control, system identification, and predictive modeling for fusion devices. His highly cited workshop report, "Advancing Fusion with Machine Learning Research Needs Workshop Report" (2020, 46 citations), helped define a strategic roadmap for the fusion community, highlighting how AI can optimize plasma performance, improve real-time control, and accelerate the path to practical fusion energy. This work has been instrumental in fostering interdisciplinary collaboration between fusion scientists and data scientists. Humphreys’ research has directly influenced the development of autonomous control systems for tokamaks and stellarators, with implications for next-generation devices like ITER. His efforts have positioned him as a key voice in the fusion-ML community, bridging experimental physics with cutting-edge computational techniques to tackle one of the most complex engineering challenges of our time.