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.
- Nicki Skafte Detlefsen does deep learning
for representation learning.
- Pablo Moreno-Muñoz works on Gaussian process models.
- Cilie Feldager (2018-2021) works with
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
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.
- Cong Geng (2020-2021) works on
geometry in generative modeling.
- Søren Wengel Mogensen (2020 - 2021)
worked on random geometries.
- Martin Jørgensen (2017-2021) studied the geometry
of latent variable models.
- Costy Kodsi (2018 - 2020)
works on numerics in geometry.
- David Eklund (2018 - 2020)
worked random Riemannian geometry.
Georgios Arvanitidis (2015-2019)
worked on learning Riemannian metrics and building statistical models accordingly.
Co-supervisor: Lars Kai Hansen.
- Tao Yang (2018) worked on manifold learning.