I combine physics-based modelling with machine learning to create robust and interpretable models. A key part of my work is linking microstructural features to macroscopic material behaviour, with applications in digital twins and advanced manufacturing.
My background is in physics and mechanical engineering, with a PhD from University of Gothenburg, where I studied multi-scale modelling of composite materials. Today, I work with approaches such as physics-informed neural networks, finite element modelling, and uncertainty quantification to improve how materials are designed and used in engineering applications.
