Luisa Eck

Part III Master student
University of Cambridge

I am a Part III Master student in Applied Mathematics at the University of Cambridge and a Master’s student in Physics at LMU Munich. I work on theoretical machine learning in my Master’s thesis with Wieland Brendel at the University of Tübingen and on theoretical condensed matter in my research project with Sergej Moroz. During my Bachelor’s studies in Physics at LMU, I spent a year abroad as a Visiting Student in Oxford attending courses in mathematical and theoretical physics.

Throughout my undergraduate and graduate studies I was supported by the Maximilianeum Foundation and the Max-Weber Programme. For my stay in Cambridge, I receive a scholarship from the German Academic Exchange Service (DAAD).



  • Quantum matter and statistical physics
  • Quantum field theory and conformal field theory
  • Probabilistic and statistical theories of learning


2020 - now University of Cambridge, MaSt Part III
statistical field theory, percolation, modern statistical methods, distribution theory
2020 - now LMU Munich, M.Sc. Physics
Master's thesis on theories for semi-supervised machine learning and domain generalization; supervision: Wieland Brendel (University of Tübingen) and Torsten Enßlin (LMU Munich)
2018 - 19 University of Oxford, Visiting MPhil student
Quantum field theory, conformal field theory, quantum matter
2017 - 20 LMU Munich, B.Sc. Physics
Theoretical condensed matter, quantum information, quantum mechanics; Bachelor’s thesis about topological quantum memories


  • Improving robustness against common corruptions by covariate shift adaptation
    Steffen Schneider*, Evgenia Rusak*, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge
    34th Conference on Neural Information Processing Systems (NeurIPS 2020)
    Exploring the Wasserstein distance as a metric for covariate shift effects.
  • On the relationship between adaptive and invariant representation learning
    Steffen Schneider*, Shubham Krishna*, Luisa Eck, Mackenzie W Mathis, Matthias Bethge
    NeurIPS 2020 Pre-Registration Workshop
    I contributed ideas to the theoretical motivation to utilize more general adaptation mechanisms as regularizers for invariant risk minimization.
  • Symmetries, phases and phase transitions of lattice spin models with gauge fields and Gauss law constraints
    Advisors: Umberto Borla, Sergej Moroz (TU Munich)
    ongoing work
  • Quasiparticle Propagation in Topological Quantum Memories
    Advisor: Belén Paredes (LMU Munich)
    Bachelor's Thesis, LMU Munich
    I reviewed the toric and surface code as physical systems governed by the Kitaev Hamiltonian and variations thereof.