CMU's Deep Survival Models Improve Fusion Reactor Disruption Prediction
nagpalchirag · x · 2026-10-01
The author developed Deep Survival Machines (DSM), a time-to-event prediction model, and the open-source Auton-Survival package during his PhD at CMU's AutonLab, originally motivated by clinical risk prediction.
A casual conversation with Cristina Rea of MIT's Plasma Science and Fusion Center led to a collaboration where PhD student Zander Keith demonstrated improved disruption prediction for fusion reactors using these deep survival models, published in Fusion Energy.
Related event: Survival Analysis Models Jump From Clinical Risk to Fusion Control(3 posts)→
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