Research group
Alumni
PhD students
2020 - 2025 (co-supervisor) Dominik Fay, Machine Learning with Decentralized Data and Differential Privacy: New Methods for Training, Inference and Sampling, subsequently Senior Research Scientist at Elekta
2019 - 2024 (co-supervisor) Niklas Gunnarsson, Motion Estimation from Temporally and Spatially Sparse Medical Image Sequences, subsequently Lead Research Scientist at Elekta
Postdocs
2022 - 2024, Zheng Zhao, subsequently Assistant Professor, Linköping University
2021 - 2024, Sebastian Mair, subsequently Assistant Professor, Linköping University
Master’s thesis students
William Samuelsson, Accelerating Interior Point Methods using Graph Neural Networks, 2025
Henri Doerks, Learning Distributed Optimization with Graph Neural Networks, 2024
Jinglin Gao, Self-supervised representation learning for Micro-CT images, 2024
Jannes van Poppelen, Phase-field modeling using physics-informed neural networks, 2024
Duc Huy Le, Exploration-Exploitation Trade-off Approaches in Multi-Armed Bandit, 2023
Benjamin Bucknall, Promoting Exploration in Reinforcement Learning through Surprise-Based Intrinsic Motivation, 2022
Dmitrijs Kass, Deep reinforcement learning for isocenter placement in Gamma Knife radiosurgery, 2022
Simon Löw, Automatic Generation of Patient-specific Gamma Knife Treatment Plans for Vestibular Schwannoma Patients, 2020
Dominik Fay, Membership Privacy in Neural Networks for Medical Image Segmentation, 2019
Kenneth Lau, Representation Learning on Brain MR Images for Tumor Segmentation, 2018
Dennis Sångberg, Automated Glioma Segmentation in MRI using Deep Convolutional Networks, 2015
Johanna Skarpman Munter, Dose-Volume Histogram Prediction using Kernel Density Estimation, 2015
Marcus Josefsson, Robust Optimization for Radiosurgery under the Static Dose Cloud Approximation, 2014
Jenni Svensson, Multiobjective optimization in radiosurgery: How to approximate and navigate on the Pareto surface, 2014
Lars Lowe Sjösund, Automatic Localization of Bounding Boxes for Subcortical Structures in MR Images Using Regression Forests, 2013