Master Thesis Projects
Several master thesis projects in machine learning are supervised at our department each year. If you are interested in pursuing such a project, feel free to contact us. Below we list a few contact persons and their ML-related research interests.
- Kristiaan Pelckmans: novelty detection, recommender systems, online machine learning, reinforcement learning, assisted daily living.
- Dave Zachariah: statistical machine learning, sparse models, online learning, dynamical systems.
- Anders Hast: handwritten text recognition, word spotting, (semi)automatic transcription.
- Olle Gällmo: neural networks, reinforcement learning, genetic algorithms, swarm intelligence.
- Joakim Lindblad: Deep Learning for Computer Vision and Pattern Recognition, Generative adversarial networks (GANs), Interpretable and Explainable AI (XAI).
- Niklas Wahlström: statistical machine learning, dynamical systems, deep learning, sensor fusion
- Orcun Göksel: deep learning in medical image analysis, image reconstruction, image translation, domain-adaptation, interpretability, life-long learning