As an assistant professor in the Pattern Recognition & Bioinformatics group of TU Delft (Delft University of Technology) I work on methodology and applications of statistical machine learning. Currently, I am particularly interested in causal inference, model evaluation/selection, philosophy of statistics/data science, domain adaptation and semi-supervised learning.
Previously I worked as a postdoc in the Data Science group of Radboud University Nijmegen on predictive and causal models for Parkinson’s disease.
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.