Field of work

My research lies in the crossing point of particle physics and data science. The Large Hadron Collider at CERN recreates the conditions of the early universe by colliding protons at ultra-high energies, allowing us to explore the secrets of the Universe. The main focus in my research is to analyse these particle collisions with the goal to discover the nature of Dark Matter, a type of matter that makes up 85% of the total matter of the Universe and that we know almost nothing about. I am currently leading the research project “Use Artificial Intelligence to pinpoint Dark Matter at the Large Hadron Collider”, financed by the research Council of Norway. In this project,  my team and I are developing new search methods to search for new physics with machine learning techniques. I have also a strong interest in, and focus on developing robust, interpretable and trustworthy AI/machine learning.

Publications

  • Machine learning classification of sphalerons and black holes at the LHC

    Grefsrud, Aurora Singstad, Buanes, Trygve, Koutroulis, Fotis, Lipniacka, Anna, Masełek, Rafał, Papaefstathiou, Andreas (2024)
  • R&D Computing, ML/AI in HEP

    Sjursen, Therese B. (2023)
  • Mixture density networks for Tau Energy Scale calibration

    Sjursen, Therese B. (2023)
  • R&D Computing, machine learning/AI

    Sjursen, Therese B. (2023)
  • Use Artificial Intelligence to pinpoint Dark Matter at the LHC

    Sjursen, Therese B. (2023)
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