As a postdoc in the Data Science group of Radboud University Nijmegen, I work on topics in and application of statistical machine learning. Currently, I am particularly interested in: causal inference, semi-supervised learning, model evaluation/selection, domain adaptation, missing data and philosophy of statistics/data science.
During my PhD I studied robust methods to do semi-supervised learning, that is: supervised models that can use additional unlabeled data with the property that, with high probability, performance is better than the original supervised model.
My PhD research was supervised by Prof. Marco Loog (affiliated with the Pattern Recognition Laboratory of the Delft University of Technology), Prof. Joost Kok (LUMC) and Prof. Eline Slagboom (LUMC) and was funded by the COMMIT research program. During my PhD I was affiliated with the Pattern Recognition & Bioinformatics group of Delft University of Technology and the Department of Molecular Epidemiology of the Leiden University Medical Center.