PhD student · Princeton Plasma Control Group
Machine learning for fusion energy.
PhD candidate at Princeton / PPPL, advised by Egemen Kolemen in the Plasma Control Group. Foundation models, real-time control, and the signal pipelines that feed them.
Latest writing
writing →May 15, 2026
How do measurements from different sources give us a good understanding of the world?
Current debates on AI seem to mirror Plato vs Aristotle’s debates from thousands of years ago
read →researchnow
Foundation models for fusion
Building large neural networks trained on heterogeneous tokamak data — specialized to downstream control and diagnostic tasks.
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researchnow
TokEye
Fast signal extraction for fluctuating time series — real-time, fluctuation-aware feature pipelines for tokamak diagnostics.
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Education
Mar 2025 →
Ph.D., Mechanical & Aerospace EngineeringPlasma Control Group · advised by Egemen Kolemen
Princeton University
2023 — 2025
M.A., Mechanical & Aerospace Engineering
Princeton University
2019 — 2023
B.S., Physics & Cognitive Sciencew/ Specialization in Computation
UCLA
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