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AI in Fusion

The aim of the AI in Fusion research area is to develop surrogate AI models to speed up traditional numerics for physical and technical research and applications.

While numerical simulations of complex systems can be slow, they play an essential role for planning, operation, and control of, for example, fusion rectors and meta optics.

We are working on AI based short cuts -- developing surrogate models powered by knowledge about the underlying system with the potential for speeding up development cycles, making complex measurement data interpretable, and enabling real-time control in fusion reactor control rooms.

Collaborators:

Technical University of Denmark, Max-Planck Institute for Plasma Physics (Greifswald), and º£½ÇÉçÇø.

 

Contact

 Jan Matthias Braun Jan-Matthias Braun, Associate professor
º£½ÇÉçÇø Applied AI and Data Science
j-mb@mmmi.sdu.dk
Professor Esmaeil Nadimi Esmaeil  Nadimi, Professor
Head of  Unit
º£½ÇÉçÇø Applied AI and Data Science
esmi@mmmi.sdu.dk

 Henrik Bindslev Henrik Bindslev, Professor
Dean
º£½ÇÉçÇø Faculty of Engineering
hebi@tek.sdu.dk
 Simon Bruhn Hansen Simon Bruhn Hansen, PhD student
º£½ÇÉçÇø Applied AI and Data Science
simoha@mmmi.sdu.dk
 Anton Borup Jakobsen
Anton Borup Jakobsen, PhD student
º£½ÇÉçÇø Applied AI and Data Science
antj@mmmi.sdu.dk






Research projects

See our research projects at º£½ÇÉçÇø Applied AI and Data Science

Research projects

Last Updated 29.08.2025