Bijnens, Bart
ICREA Research Professor at Fundació de Recerca Clínic Barcelona-Institut d'Investigacions Biomèdiques August Pi i Sunyer (FRCB-IDIBAPS).
Engineering Sciences
Short biography
Bart Bijnens obtained an MSc in Electronic Engineering and PhD in Medical Sciences (1997, KULeuven, Belgium). He was tenured Professor of Cardiovascular Imaging&Dynamics at the Medical Faculty in Leuven (1998-04), supervised clinical research at St. George's Hospital in London (2005-6) and was resident Visiting Professor at the University of Zagreb (2007), Croatia. Since Sept. 2008, he is ICREA Research Professor in Barcelona, first at the UPF and currently at IDIBAPS, leading the 'Translational Computing in Cardiology' group. He is recognised as international expert in pathophysiological concepts and (image-based) assessment of CV diseases, with a reputation of being able to explain basic pathophysiology principles and put technical developments in context. This resulted in many international collaborations/publications/lectures as well as being requested by centres all over the world for advice on research in cardiovascular mechanics and imaging.
Research interests
Translational Cardiovascular Pathophysiology, focussing on assessing cardiac function and understanding changes induced by disease and how treatment can modulate this remodelling. This is approached by integrating information handling and computing, combined with basic pathophysiology knowledge in order to advance clinical sciences. This implies an approach from basic understanding of disease towards a clinical study; selecting/designing appropriate investigational tools to assess relevant clinical parameters; quantifying diagnostic information (from clinical information to imaging data) to extract pertinent information and interpreting results and relate them to pathophysiology. Recent projects include the combination of computational modelling with interpretable machine learning in order to find easy to implement/deploy techniques for the identification of patients at risk for adverse events, as well as to improve our understanding of disease and decission making.