People

I'm fortunate to work with excellent people; meet some of them here.

Meet awesomeness!

Many great people have decided to work with me on various projects. I'm truly grateful to these individuals for enriching my working life so much. If you're interested in joining the ranks of these amazing people as a PhD student or post doc, then check the open positions. If you're interested in a master's project, then just contact me.

Post docs

  • David Eklund (2018 - 2020) works random Riemannian geometry.
  • Costy Kodsi (2018 - 2020) works on numerics in geometry.

PhD students

  • Georgios Arvanitidis (2015-2018) works on learning Riemannian metrics and building statistical models accordingly. Co-supervisor: Lars Kai Hansen.
  • Nicki Skafte (2017-2020) does deep learning for estimating metrics. Co-supervisor: Ole Winther.
  • Martin Jørgensen (2017-2020) studies the geometry of latent variable models. Co-supervisor: Lars Kai Hansen
  • Cilie Feldager (2018-2021) works with random metrics. Co-supervisor: Lars Kai Hansen
  • Jeppe Thagaard (2018-2021) works with cell and tissue classification. Main supervisor: Anders Dahl.
  • Dimitris Kalatzis (2018-2021) works with generative models. Co-supervisor: Ole Winther.

Research assistants

  • Pola Elisabeth Schwöbel (2018-2019) works on data augmentation and related topics.

Master students

  • Anne Sofie Talleruphuus (2018) works on data augmentation.
  • Christian Hjuler Christensen (2018) works on data augmentation.
  • Daniel Beck Hansen (2018) works on data augmentation.
  • Bue Jul Jørgensen (2018) works on data augmentation.

Alumni

  • Tao Yang (post doc, 2018) worked on manifold learning.
  • Asger Ougaard (master student, 2018) worked on data augmentation.
  • Tobias Slott Jensen (master student, 2018) worked on data augmentation.
  • Dan Olsen (master student, 2017) worked on directional statistics.
  • Jeppe Thagaard (master student, 2017) worked on deep learning for histopathology.
  • Nicki Skafte (master student, 2017) worked on diffeomorphisms in deep learning.