Summary
Dr. Chris Cantwell is a Senior Lecturer in the Department of Aeronautics at Imperial College London, United Kingdom. Dr. Cantwell received an MMath in Mathematics in 2005 and an MSc in Scientific Computing in 2006, from the University of Warwick. He received a PhD in Scientific Computing in 2009, also from the University of Warwick, investigating the stability and transient growth of perturbations in fluid flow. He moved to Imperial College London developing high-order spectral/hp element methods, followed by a discipline-hop award from the British Heart Foundation to develop an interdisciplinary research programme in the field of cardiac electrophysiology and is a founding member of the ElectroCardioMaths programme, part of the Imperial College Centre for Cardiac Engineering.
Dr. Chris Cantwell’s research is centred around developing novel and scalable numerical approaches for efficiently modelling and understanding complex physical processes in the aerodynamics and biomedical domains. Much of his work to date has focused on the efficient implementation and application of spectral/hp element methods for performing high-fidelity numerical simulation and making these tools more accessible to users without a detailed understanding of the numerical methods. However, his research interests now extend to the fusion of numerical modelling with statistical methods and machine learning. He is a strong proponent of open-source software and is a project leader of the Nektar spectral/hp element framework which acts as a vehicle for much of his research.
Publications
Journals
Lino M, Fotiadis S, Bharath AA, et al., 2023, Current and emerging deep-learning methods for the simulation of fluid dynamics, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol:479, ISSN:1364-5021
Kim MY, Nesbitt J, Koutsoftidis S, et al., 2023, Immunohistochemical characteristics of local sites that trigger atrial arrhythmias in response to high frequency stimulation, Ep Europace, Vol:25, ISSN:1099-5129, Pages:726-738
Lino M, Fotiadis S, Bharath AA, et al., 2022, Multi-scale rotation-equivariant graph neural networks for unsteady Eulerian fluid dynamics, Physics of Fluids, Vol:34, ISSN:1070-6631
Coveney S, Cantwell C, Roney C, 2022, Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate, Medical & Biological Engineering & Computing, Vol:60, ISSN:0140-0118, Pages:2463-2478
Conference
Lindblad D, Sherwin SJ, Cantwell C, et al., 2023, Large Eddy simulations of isolated and installed jet noise using the high-order discontinuous Galerkin method, AIAA SCITECH 2023 Forum, American Institute of Aeronautics and Astronautics, Pages:1-21