Teaching & Supervision

Courses

Ongoing / upcoming

  • Fall 2026: Medical Image Analysis, Department of Computer Science, University of Copenhagen (course responsible).
  • 2026: Quantitative Reproducible Data Science, specialized PhD course, DIKU, with Cyril Pernet.

Previously

  • Spring 2026: Computational Methods in Simulation (CMIS), DIKU (course responsible).
  • Fall 2025: Medical Image Analysis, DIKU (course responsible).
  • Spring 2025: Computational Methods in Simulation (CMIS), DIKU (course responsible).
  • 2025: Quantitative Reproducible Data Science, specialized PhD course, DIKU, with Cyril Pernet.
  • Fall 2024: Medical Image Analysis, DIKU (course responsible).
  • Spring 2024: Computational Methods in Simulation (CMIS), DIKU (course responsible).
  • 2024: Quantitative Reproducible Data Science, specialized PhD course, DIKU, with Cyril Pernet.
  • Fall 2023: Medical Image Analysis, DIKU (course responsible).
  • Spring 2023: Computational Methods in Simulation (CMIS), DIKU, with Kenny Erleben.
  • 2023: Quantitative Reproducible Data Science, specialized PhD course, DIKU, with Cyril Pernet.
  • Fall 2022: Medical Image Analysis, DIKU (course responsible).
  • Spring 2022: Data analysis and machine learning for secondary school teachers (Masteruddannelsen i informatikundervisning); "Automatiseret billedanalyse" module in Digital Health and Data continuing education (Danish); Computational Methods in Simulation (CMIS), DIKU, with Kenny Erleben.
  • Fall 2021: Medical Image Analysis, DIKU (course responsible).
  • Spring 2021: Computational Methods in Simulation (CMIS), DIKU, with Kenny Erleben.
  • Fall 2020: Medical Image Analysis, DIKU (course responsible).
  • Spring 2020: Computational Methods in Simulation (CMIS), DIKU, with Kenny Erleben.
  • Fall 2019: Medical Image Analysis, DIKU, with Sune Darkner.
  • Spring 2019: Computational Methods in Simulation (CMIS), DIKU, with Kenny Erleben.
  • Fall 2018: No teaching due to maternity leave.
  • Spring 2018: Computational Methods in Simulation (CMIS), DIKU, with Kenny Erleben.
  • Fall 2017: Medical Image Analysis, DIKU, with Sune Darkner; Health Care Technology, DIKU and DTU, with Rasmus R. Paulsen.

Supervision

I supervise Bachelor's and Master's projects — please get in touch if you are interested.

PostDoc supervision

  • Alissa Valentine, TRUSTMIND, 2025–2027, DIKU.
  • Helen Coupland, Lundbeck Experiment / TRUSTMIND, 2025–2026, NRU, Rigshospitalet.
  • Madeleine Wyburd, NIBS-CP, 2025–2027, DIKU.
  • Llucia Coll Benejam, BrainDrugs WP5, 2025–2027, NRU, Rigshospitalet.
  • Martina Finocchiaro, IRE EU project, 2024–2026, DIKU.
  • Vincent Beliveau, BrainDrugs WP5, 2021–2024, NRU, Rigshospitalet.
  • Eike Petersen, Bias and fairness in medicine, 2021–2023, DTU & NRU, Rigshospitalet.
  • Sreejita Ghosh, Bias and fairness in medicine, 2021, DTU & NRU, Rigshospitalet.
  • Martin Nørgaard, OpenNeuroPET, 2019–2020, NRU, Rigshospitalet.
  • Vincent Beliveau, NRU atlas project, 2018–2019, NRU, Rigshospitalet.

PhD student (co-)supervision

See also the NRU PhD projects page.

  • Alice Schiavone, "Trustworthy AI in Healthcare: Fairness, Uncertainty, and Robust Evaluation of Machine Learning Models", 2026–2029, DIKU.
  • Martin Christian Emanuel Prener, "Real-world epilepsy outcomes from electronic health records: seizure trajectories, treatment failure, and large language model extraction", 2026–2029, KU SUND (co-supervisor).
  • Ruben Dörfel, "Developing and evaluating new and existing models for brain-age prediction", 2023–2027, Karolinska Institutet (co-supervisor).
  • Giske Opheim, "Severe epilepsy – a new era in the presurgical evaluation by ultra high field MR at 7 Tesla", 2017–2020, KU SUND (co-supervisor).
  • Martin Nørgaard, "Optimizing Preprocessing Pipelines in PET/MRI Neuroimaging", 2016–2019, KU SUND (co-supervisor).
  • Vincent Beliveau, "Brain connectivity of the serotonergic system", 2015–2017, KU SUND (co-supervisor).

Selected Bachelor's / Master's theses

  • Sofie Lionet Faxholm, "Investigating Bias in Evaluation Metrics under Cross-Validation", Master's thesis, spring 2026, KU MATH.
  • Marcus Nygaard Skovgaard Rasmussen, "Predicting Infant Brain Age from Structural MRI", Master's thesis, spring 2026, DIKU.
  • August Toft Bentsen, "Fairness in Machine Learning for Mental Healthcare", Master's thesis, spring 2026, KU SUND.
  • Anna Filippa Biil, "Improving automatic methods for segmenting infant MRI scans over a wide age range", Master's thesis, fall 2025, DIKU.
  • Manuel Wegmann, "Machine Learning for Longitudinal Brain Age Prediction", Master's thesis, spring 2025, DIKU (with Ruben Dörfel).
  • Magnus Lindberg Christensen, "FmapSynth: Deep Learning-Based Fieldmap Synthesis for BOLD fMRI Distortion Correction", Master's thesis, spring 2025, DIKU (with Patrick Fisher).
  • Jakob Sheye & Hvristo Georgiev, "Generative Models for Children’s Head Motion in Resting-State fMRI", Master's thesis, spring 2024, DIKU.
  • Mads Daugaard & Emil Christoffer Riis-Jacobsen, "Simulating Human Movement in MRI: A Soft Phantom Head Approach with Machine Learning Integration", Master's thesis, spring 2024, DIKU.
  • Jingyu Huang, "Contrast-agnostic segmentation of deep brain nuclei in magnetic resonance images", Master's thesis, spring 2023, DIKU.
  • Avneet Kaur, "Development of a robust and reproducible preprocessing pipeline for PET data", Master's thesis, fall 2021, DIKU.
  • Hannah Eichhorn, "Comparison of prospective and retrospective motion correction for MRI", Master's thesis, fall/winter 2020, NBI KU.
  • Andreea-Veronica Vascan, "How do children move in the MR scanner with and without anaesthesia?", Master's thesis, winter 2019, DIKU.
  • Emily Barot, "Optimization of Voxelwise and Surface-Based Preprocessing Pipelines for PET Data", Master's thesis, spring 2019, DIKU.

This is a selection — many more Bachelor's and Master's students have been supervised since 2010. Get in touch for the full list.