About me

I am an assistant professor at the data science group of the Institute for Computing and Information Sciences, Radboud University Nijmegen. I am interested in combining mechanistic and machine learning methods, uncertainty quantification, and various time series applications (inspired by the fields of bioinformatics, genomics, and econometrics, but not limited to them). My latest research is closely connected to Gaussian processes and physics-informed machine learning.

Previously I worked as a postdoc in the machine learning group of prof. Tom Heskes at the Institute for Computing and Information Sciences, Radboud University Nijmegen. My research during this period focused on probabilistic machine learning for drug-drug interaction and mixture toxicity data. Before joining Radboud University, I worked as a research associate in the group of prof. Magnus Rattray, where I was first exposed to Gaussian processes (GPs), and I continue this line of research up to this day. I received my PhD from Maastricht University with the thesis “Bayesian inference in multivariate nonlinear state-space models”, supervised by dr. Michael Eichler.