As a researcher at the Cardiovascular Research Institute Maastricht, I investigate how we can measure and quantify the properties of the cardiac arrhythmia atrial fibrillation, or AF in short. I have particular interests in signal processing, parameter estimation and machine learning techniques applied to the assessment of the complexity of AF and the prediction of AF progression and outcome, using both measurements obtained directly from the atria, as well as noninvasive measurements such as the electrocardiogram (ECG).

Recently I have started to develop and implement a systems biology approach to the understanding of AF, which is aimed at linking differences in atrial gene expression profiles, as determined by next generation RNA sequencing, to tissue characteristics and patient phenotype.

My ambition is to develop a multiscale, patient-specific understanding of AF: starting from the genome and atrial tissue characteristics, all the way up to the electrophysiological properties of the conduction on the atrium and the projection of these conduction patterns on the body surface of a patient, as measured by the ECG.