Andreas Gillgren
Andreas is a PhD Student in Plasma Physics and Fusion Energy. His research focuses on Machine Learning and its applications for magnetic confined fusion devices.
Showing 9 publications
Data-driven models in fusion exhaust: AI methods and perspectives
High temporal resolution of pedestal dynamics via machine learning on density diagnostics
Machine learning applications for predicting the pedestal in tokamak plasmas
A fast neural network surrogate model for the eigenvalues of QuaLiKiz
Enabling adaptive pedestals in predictive transport simulations using neural networks
Disruption prediction with artificial intelligence techniques in tokamak plasmas
Enhanced performance in fusion plasmas through turbulence suppression by megaelectronvolt ions
Overview of JET results for optimising ITER operation
Towards understanding reactor relevant tokamak pedestals
Download publication list
You can download this list to your computer.
Filter and download publication list
As logged in user (Chalmers employee) you find more export functions in MyResearch.
You may also import these directly to Zotero or Mendeley by using a browser plugin. These are found herer:
Zotero Connector
Mendeley Web Importer
The service SwePub offers export of contents from Research in other formats, such as Harvard and Oxford in .RIS, BibTex and RefWorks format.