From clinical risk prediction to fusion plasma control: the Deep Survival Machines story
nagpalchirag · x · 2026-10-01
The author (PhD at CMU's Auton Lab / SCS) traces how his research crossed from clinical prediction into fusion:
- During his PhD he developed Deep Survival Machines (DSM), a time-to-event prediction model originally motivated by clinical risk prediction, plus Auton-Survival, an open-source deep learning package for survival analysis.
- A casual conversation with Cristina Rea at MIT's Plasma Science and Fusion Center grew into a collaboration where PhD student Zander Keith demonstrated improved disruption prediction with these models, published in Journal of Fusion Energy.
- The thread includes references to follow-up work: AI control on the DIII-D tokamak, real-time plasma monitoring frameworks, and horizon-aware disruption alarm prediction (2024–2026).
A full arc of clinical ML methods ending up supporting AI control of fusion devices.
Related event: Survival Analysis Models Jump From Clinical Risk to Fusion Control(3 posts)→
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