Machine Learning
Facilitating research collaborations between divisions and between the department of Information technology and external parts.
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.
Contact persons
- 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