I am a PhD Fellow of Machine Learning with the Department of Computer science at the University of Copenhagen, co-advised by Aasa Feragen and Oswin Krause.
My PhD research focuses on developing deep learning methods for medical imaging, with a focus on image registration. In my work I dive into unsupervised & semi-supervised learning, with an emphasis on the registration of tricky, real-world anatomies and an ambition to develop general algorithms that apply to a multitude of problem domains and modalities. I also published on uncertainty quantification and topology detection.
Previously, I obtained a M.Sc. in computer Science from the University of Copenhagen. During my Masters I worked tgether with the LEGO group on teaching reinforcement learning with LEGO Mindstorms Robots, and designed a lightweight perceptual similarity metric for image generation and distance measuring, advised by Christian Igel.
Selected publicationsFind the full list here
NeurIPSA Loss Function for Generative Neural Networks Based on Watson’s Perceptual ModelIn Advances in Neural Information Processing Systems Dec 2020
NeurIPSSpot the Difference: Detection of Topological Changes via Geometric AlignmentIn Advances in Neural Information Processing Systems Dec 2021
MIDL AwardSemantic similarity metrics for learned image registrationBest Paper Award Runner-UpIn Proceedings of Machine Learning Research Jul 2021