Mark D. Boyer

Princeton Plasma Physics Laboratory

Papers

1

Total Citations

46

H-Index

1

About

Mark D. Boyer is a leading researcher at the intersection of fusion energy science and machine learning, where his work is helping to accelerate the path toward practical fusion power. His primary contributions center on integrating advanced computational methods—particularly machine learning and artificial intelligence—into the analysis, control, and optimization of fusion plasma experiments. Boyer’s highly collaborative approach is exemplified by his role in the "Advancing Fusion with Machine Learning Research Needs Workshop Report" (2020, 46 citations), a landmark document that systematically identified the most promising opportunities for ML/AI to solve critical challenges in fusion research, from real-time plasma control to predictive modeling of instabilities. This workshop report has become a foundational reference for the growing community of researchers working at this interdisciplinary frontier. Beyond this influential synthesis, Boyer is recognized for developing and applying data-driven techniques to improve the performance and reliability of tokamak operations, bridging the gap between traditional physics-based models and modern machine learning tools. His work is shaping how the next generation of fusion experiments will be designed and controlled.

Research Focus

Key Achievements

1
H-Index
1
Papers
46
Total Citations
46
Avg Citations/Paper
🏆 Most Cited Paper
Advancing Fusion with Machine Learning Research Needs Workshop Report
46 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Princeton Plasma Physics Laboratory

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago