About Me
I am a machine learning researcher and engineer with a PhD from Chalmers University of Technology, where my work explored how machine learning can support decision-making in healthcare. Since October 2025, I have been working as a Data Scientist at Ericsson, focusing on generative AI and large language model training.
Education
PhD in Machine Learning
Chalmers University of Technology
MSc in Engineering Physics
Chalmers University of Technology
Research Interests
- Sequential Decision-Making
- Interpretable Machine Learning
- Off-Policy Evaluation
Recent News
- [Oct 2025] I am excited to be joining Ericsson as a Data Scientist! I will be working in their Generative AI Lab, training custom LLMs to improve internal code efficiency.
- [Sept 2025] I successfully defended my PhD thesis on August 27 – officially Dr. Matsson! 🎓
- [Aug 2025] I will defend my PhD thesis, Interpretable Machine Learning for Modeling, Evaluating, and Refining Clinical Decision-Making, on August 27 at 09:00 in HA2, Hörsalsvägen 4. The faculty opponent will be Research Scientist Li-wei H. Lehman from the Institute for Medical Engineering & Science (IMES) at MIT. More information is available here.
- [July 2025] A preprint of my paper on pragmatic policy development is now available on arXiv.
- [May 2025] My paper on missingness-avoiding machine learning has been accepted to ICML 2025 for a spotlight poster presentation.
Recent Publications
(2025).
Interpretable Machine Learning for Modeling, Evaluating, and Refining Clinical Decision-Making.
Doctoral dissertation.
(2025).
Pragmatic Policy Development via Interpretable Behavior Cloning.
arXiv preprint.
(2025).
Prediction Models That Learn to Avoid Missing Values.
To appear in Proceedings of the 42nd International Conference on Machine Learning.
(2024).
How Should We Represent History in Interpretable Models of Clinical Policies?.
In Proceedings of the 4th Machine Learning for Health Symposium.
(2024).
Unsupervised Domain Adaptation by Learning Using Privileged Information.
Transactions on Machine Learning Research.