Next Step Fusion Publications
We're driven to advance fusion towards commercialization and to benefit humanity. While we can't always publish or present results from commercial customer projects, we always aim to share more about our technologies and work.
If you see anything you'd like to discuss, please contact us.
If you see anything you'd like to discuss, please contact us.
- PUBLICATIONS
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2025
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Plasma Confinement State Classification via FPP Relevant Microwave Diagnostics
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Robustness by Design: Interface Contracts for AI Control in High-Stakes Physical Systems
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Reconstruction-free magnetic control of DIII-D plasma with deep reinforcement learning
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Summary report from the mini-conference [APS DPP 2024] on Digital Twins for Fusion Research
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Reconstructing the Plasma Boundary with a Reduced Set of Diagnostics
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Validation of NSFsim as a Grad-Shafranov Equilibrium Solver at DIII-D
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Electromagnetic System Conceptual Design for a Negative Triangularity Tokamak
Abstract - POSTERS
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2025
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[APS DPP 2025] Machine Learning Approaches to Plasma State Mode Classification via Reactor Relevant Diagnostics at DIII-D
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[APS DPP 2025] Integrated tokamak control using NSFsim simulator
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[FEC 2025] Fusion Twin Platform: An Innovative Tool for Fusion Research and Education
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[FEC 2025] Reconstructing the Plasma Boundary with a Reduced Set of Diagnostics
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[EPS 2025] Fusion Twin Platform: An Innovative Tool for Fusion Research and Education
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[EPS 2025] Design and Implementation of a Reinforcement Learning-based Plasma Shape Controller at DIII-D
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[EPS 2025] NSFsim Code for Machine Design and Scenario Development
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[OSSFE 2025] Developing a State-Oriented Plasma Control System
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2024
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[APS DPP 2024] NSFsim Validation as a DIII-D Plasma Equilibrium Simulator
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[EPS 2024] Validation and Verification of Synthetic Magnetic Diagnostics Based on Free Boundary Equilibrium Solver for DIII-D Plasma Control System
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[EPS 2024] Electromagnetic System Conceptual Design for a Negative Triangularity Tokamak
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[EEML 2024] Magnetic feedback control of DIII-D tokamak via deep reinforcement learning
Abstract - PRESENTATIONS
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2025
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[PhDiaFusion 2025] Novel tools for tokamak design and control
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Plasma Control Online Meetup - May 6th, 2025
Plasma Control Online Meetup videos:- Georgy Subbotin (Next Step Fusion), "Controlling fusion plasma with reinforcement learning"
- Adriano Mele (Swiss Plasma Center at EPFL), "Case Study: Application of Model Predictive Control to the Plasma Shape in TCV"
- Sara Dubbioso (Consorzio CREATE), "Data-driven and model free approaches for magnetic control"
- Vacslav Glukhov (Next Step Fusion), "Multi-Objective Optimization and Control of Plasma States"
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[AI4X 2025] Magnetic control of tokamak plasma through deep reinforcement learning with privileged information
- OTHER
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Tech Blog
Our tech blog is a valuable source of information about our work and our thoughts on the fusion industry. Note that we also cross-post it as a LinkedIn newsletter.
Read on Medium
LinkedIn Newsletter -
LinkedIn
