prof. dr. M. (Michiel) Rienstra

Michiel Rienstra is a Clinical Cardiologist, Professor of Clinical Cardiology and Clinical Director at the University Medical Center Groningen, the Netherlands.

Graduated in medicine at the University of Antwerp, Belgium in 2003. Obtained a PhD at the University of Groningen, The Netherlands in 2007 on Atrial Fibrillation, Underlying Disease and Prognosis. He completed his cardiology training at the University Medical Center Groningen in 2012, where continued working as clinical cardiologist and researcher. He was awarded with a NWO Rubicon grant in 2009 and went to Harvard Medical School, Massachusetts General Hospital and the Framingham Heart Study for a post-doc on population genetics and epidemiology in 2010-2011. In 2012 he was awarded with the NWO Veni grant for my project on genetics of atrial fibrillation. In 2015 he received the European Society of Cardiology academic grant for his project on a big data approach in atrial fibrillation. He was work package leader of 3 large national consortia (all funded by Dutch Heart Foundation); RACE V (hypercoagulability and AF progression), RED-CVD (early detection of cardiovascular disease in general practices), AI (catalyzing the application of artificial intelligence in CV disease), and is work package leader of the national MyDigiTwin consortium (Big-data and Artificial Intelligence-based ecosystem to create a user’s personal “Digital Twin”), and principal investigator of the national EmbRACE (Electro-Molecular Basis and the theRapeutic management of Atrial Cardiomyopathy, fibrillation and associated outcomEs) network (funded by Dutch Heart Foundation). He is/was steering committee member of several investigator-initiated clinical studies (RACE 2 to 10, MARC 1-2, VIP-HF 1-2, DECISION). He is fellow of the European Society of Cardiology and the American Heart Association, member of European Heart Rhythm Association.

He combines clinical cardiology focusing on treatment of patients with arrhythmias, with clinical-oriented research. His research consists of conducting clinical studies to improve AF treatment, studying epidemiology of AF and its risk factors in PREVEND, Lifelines and Framingham Heart Study, uncovering the genetics of atrial fibrillation in part with the international AFGen consortium, and applying machine learning/artificial intelligence tools to improve AF risk prediction.