Funded research, grants and computing resources, from an EU digital-twin project to federated learning frameworks.
Integrated modelling for sustainable and optimized steel manufacturing. A demonstration platform that predicts and visualizes the best use of the processing steps in a steel manufacturing chain, coupling them through numerical simulation, soft sensors and distributed machine learning.
Advancing the university's research and education within artificial intelligence.
An open-source, modular and ML-framework-agnostic system for federated machine learning, supporting highly scalable cross-silo and cross-device use cases.
A federated database integrating major research data sources for privacy-preserving analysis of Swedish register data, built as a scalable research testbed.
New algorithms for extracting and ranking association rules from big transportation data, applied to road safety in Morocco.
EU Horizon Europe, Clean Steel Partnership · Grant 101178721
Select-ML · University of Skövde
SNIC AI/ML 2021 · SNIC cloud resources
UPPMAX 2021/2-4 · SNIC cloud resources
Wallenberg Foundation
Libraries and research code from these projects.
I am interested in collaborative proposals for EU programmes (Horizon Europe, Marie Skłodowska-Curie Actions and others) and national funding agencies, as a research partner, co-investigator or consortium member.
