• Julia Machnio (Ph.D., University of Copenhagen, 2024–)
  Project title: A fine-grained analysis of brain imaging abnormalities using active learning
  Paper 1 • Paper 2

• Ida Brandt Andersen (Ph.D., University of Copenhagen, 2024–)
  Project title: Predicting risk of surgery, tumor growth, and endocrine failure using AI

• Aida Moafi (Ph.D., University of Leicester, 2024–)
  Project title: Cardiac fibrosis and scar segmentation from MRIs using deep learning
  Paper 1

• Gabriel Sainz Vazquez (M.Sc., University of Copenhagen, 2025–)
  Project title: Counterfactual brain MRI generation with deep generative models

• Sara Leiva Montoya (B.Sc., Universidad de los Andes, 2025)
  Project title: Image segmentation using pretrained foundation models

• Ziwen Xiong (M.Sc., University of Copenhagen, 2025)
  Project title: Deep learning for neuronal activity analysis under heat stress in zebrafish

• Daniel Vilet Rodríguez (M.Sc., University of Copenhagen, 2025)
  Project title: MRI-based cognitive decline prediction using pretrained foundation models

• Nathaniel Putera (M.Sc., University of Copenhagen, 2025)
  Project title: Cognitive decline clustering and prediction in multimodal Alzheimer’s disease cohorts

• Markos Aivazoglou Vounatsos (M.Sc., University of Copenhagen, 2025)
  Project title: High-quality image synthesis using efficient denoising diffusion models

• Simon Winther Albertsen (B.Sc., University of Copenhagen, 2025)
  Project title: Multiscale medical image segmentation with deep learning models

• Hjalte Svaneborg Bjørnstrup (B.Sc., University of Copenhagen, 2025)
  Project title: Multiscale medical image segmentation with deep learning models

• Said Djafar Said (B.Sc., University of Copenhagen, 2025)
  Project title: Brain MRI generation with guidance, explainability, and privacy inspection

• Milla E. Nielsen (B.Sc., University of California, Los Angeles, 2024)
  Project title: Alzheimer’s disease detection from MRI biomarkers using machine learning methods
  Paper 1

• Casper Lisager Frandsen (M.Sc., University of Copenhagen, 2024)
  Project title: Multimodal (CT-MRI) registration of brain imaging using deep learning methods

• Karl van Eeden Risager (B.Sc., University of Copenhagen, 2024)
  Project title: Quality assessment of brain imaging-based generative AI models
  Paper 1

• Noah Videcrantz (B.Sc., University of Copenhagen, 2024)
  Project title: Reconstructing 3D brain images for domain adaptation using deep learning

• Nikolaj Søberg Lerke (B.Sc., University of Copenhagen, 2024)
  Project title: Inspecting privacy preservation in generative medical imaging

• Jonas Møller Bagger (B.Sc., University of Copenhagen, 2024)
  Project title: Deep learning-based image retrieval from non-imaging records

• Nicole Kozlová (M.Sc., University of Copenhagen, 2023)
  Project title: Multimodal brain MRI segmentation using deep learning-based registration

• Holger Rubæk Danielsen (B.Sc., University of Copenhagen, 2023)
  Project title: Concept bottleneck models on brain pathology

• Alice Schiavone (M.Sc., University of Milan, 2023)
  Project title: Segmentation and detection of white matter hyperintensities in uncontrolled settings
  Paper 1

• Sebastian Nørgaard Llambias (M.Sc., University of Copenhagen, 2022)
  Project title: Unsupervised domain adaptation for medical imaging using data augmentation
  Paper 1 • Paper 2 • Paper 3

• Amaro Garcia Suarez (M.Sc., University of Copenhagen, 2022)
  Project title: Texture-based analysis of the hippocampus for Alzheimer’s disease prediction using 2D CNNs

• Kiril Vadimovic Klein (M.Sc., University of Copenhagen, 2022)
  Project title: Brain volumetric changes due to COVID-19 – A retrospective study on a Danish cohort
  Paper 1 • Paper 2

• Neus Rodeja Ferrer (M.Sc., University of Copenhagen, 2022)
  Project title: Cerebral microbleeds on brain MRI of COVID-19 patients – A retrospective cohort study
  Paper 1 • Paper 2

• Mehdi Mehdipour Ghazi (M.Sc., Science and Research, 2020)
  Project title: Traffic flow prediction and optimization with incomplete data using deep learning methods
  Paper 1 • Paper 2