Work with me on federated learning
Open topics for PhD and master's students, and how to apply. I also co-supervise theses with industry partners.
Who I work with
PhD students
Doctoral positions are advertised by the university when funding is available. Watch the News page for openings.
Master's students
Students at Skövde and partner universities looking for a thesis in AI, data science or federated learning.
Industry partners
Companies interested in privacy-preserving AI, joint projects, or co-supervising a thesis.
Open research topics
Starting points for a thesis. Each builds on ongoing work in my group.
Robust federated learning
Defending federated training against label flipping, backdoors and other poisoned clients.
Federated learning for medical imaging
Training diagnostic models across hospitals on the edge, without sharing patient data.
Federated fine-tuning of LLMs
Personalising large language models for specific domains while keeping data private.
Distributed AI for digital twins
Soft sensors and distributed learning for industrial processes such as steel manufacturing.
Efficient learning at the edge
Making federated training fit the compute, memory and network limits of edge devices.
Multi-criteria decision analysis
Robust rankings and sensitivity analysis for decision support, building on mcdakit.