Kevin Mulder

Postdoctoral Fellow

University College London

Kevin completed his PhD within the UCL Center for Doctoral Training (UCL) in Data Intensive Science (DIS) funded by the Royal Society on the NUMI Off-axis $\nu_e$ Appearance (NOvA) and NOvA Testbeam experiments. The research mainly focussed on the robustness improvement of the convolutional neural networks employed in these experiments for the purposes of reconstruction and classification of neutrino events, in the presence of systematic uncertainties through domain adaptation techniques.

Kevin is part of the Learned Exascale Computational Imaging (LEXCI) project working on a variety of topics, including artificial intelligence and inverse problems on the spherical domain.


  • Neutrino Oscillations
  • Convolution Neural Networks
  • Domain Adaptation
  • Inverse Imaging Problems
  • Geometric AI on the Sphere


  • PhD in Data Intensive Science

    University College London

  • MSc in Physics

    King's College London

  • BS in Applied Physics

    Eindhoven University of Technology