After my bachelors in Civil Engineering at The Hague University of Applied Sciences, I obtained my MSc in Structural Engineering at TU Delft. In my thesis, I combined manifold learning and Bayesian neural networks to optimize the microstructures of composite materials. Currently, I am a PhD candidate in the SLIMM AI Lab, where we use machine learning techniques to improve material modeling.
My research aims to accelerate multiscale mechanical models, making it feasible to study materials more accurately. I am applying machine learning techniques in combination with computationally expensive physics-based models. An essential part of this research is balancing the speed of machine learning techniques with the accuracy and stability of traditional models by identifying the uncertainty of surrogate models in an active-learning scheme.
Further interests include mesh-based graph neural networks, physics-informed machine learning, uncertainty quantification, and concurrent multiscale modeling.
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