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

PhD students

  • Nicki Skafte (2017-2020) does deep learning for estimating metrics. Co-supervisor: Ole Winther.
  • 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.
  • Pola Elisabeth Schwöbel (2019-2021) works on bias in machine learning. Co-supervisor: Kristoffer Hougaard Madsen.
  • Frederik Warburg (2020-2022) works on place recognition. Co-supervisor: Søren Gregersen.
  • Alison Pouplin (2020-2023) works on random Riemannian geometry. Co-supervisor: David Eklund.
  • Yevgen Zainchkovskyy (2020-2023) works on Bayesian optimization. Co-supervisor: Carsten Stahlhut.
  • Giorgio Giannone (2020-2023) works on generative models. Main supervisor: Ole Winther.
  • Jakob Drachmann Havtorn (2020-2023) works on generative models. Main supervisor: Jes Frellsen. Co-supervisors: Ole Winther, Lars Maaløe.
  • Hadi Beik-Mohammadi (2020-2023) works on geometry in robotics. Main supervisor: Leonel Rozo (Bosch). Co-supervisor: Gerhard Neumann.
  • Federico Bergamin (2020-2023) works on generative models for recommender systems. Main supervisor: Jes Frellsen.

Visiting scholars

  • Cong Geng (2020-2021) works on geometry in generative modeling.


  • Costy Kodsi (post doc, 2018 - 2020) works on numerics in geometry.
  • David Eklund (postdoc, 2018 - 2020) worked random Riemannian geometry.
  • Georgios Arvanitidis (PhD, 2015-2019) worked on learning Riemannian metrics and building statistical models accordingly. Co-supervisor: Lars Kai Hansen.
  • Tao Yang (postdoc, 2018) worked on manifold learning.