Dr. Chris Cantwell’s research is highly interdisciplinary, bridging numerical modelling, signal processing, clinical data, medical imaging and basic laboratory science. His current area of interest is to use engineering techniques to address the biomedical challenges in clinical cardiac electrophysiology.
Chris Cantwell obtained a First Class honours degree in Mathematics at the University of Warwick in 2005. He subsequently completed an MSc and PhD in Scientific Computing at the University of Warwick's Centre for Scientific Computing, studying the transient growth of small disturbances to fluid flow in a linearly stable regime. He moved to Imperial College London to join Professor Spencer Sherwin’s group, initially developing high-order spectral/hp element methods, before being awarded a 3-year Advanced Training Award from the BHF with which he transitioned to address challenges in the understanding and treatment of atrial arrhythmias.
et al., Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling
et al., Determinants of new wavefront locations in cholinergic atrial fibrillation, Ep-europace, ISSN:1099-5129
Cantwell CD, Nielsen AS, 2018, A Minimally Intrusive Low-Memory Approach to Resilience for Existing Transient Solvers, Journal of Scientific Computing, ISSN:0885-7474
et al., 2018, A novel approach to mapping the atrial ganglionated plexus network by generating a distribution probability atlas., J Cardiovasc Electrophysiol
et al., 2018, Analytical approaches for myocardial fibrillation signals., Comput Biol Med