Dr Stef Zeemering studied Knowledge Engineering at Maastricht University and graduated with a master in Operations Research. After working in the industry as a mathematical consultant, he went on do a PhD at Maastricht University on the topic of sparse optimisation in mathematical systems theory. After a brief return to industry as a scientific software engineer at Maastricht Instruments, he joined the Department of Physiology in 2011. As a post-doc, he investigates how we can measure and quantify the properties of atrial fibrillation (AF). He has 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, he 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. His 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.