Imperial College London

Dr Chris Cantwell

Faculty of EngineeringDepartment of Aeronautics

Senior Lecturer in Aeronautics
 
 
 
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Contact

 

+44 (0)20 7594 5050c.cantwell Website

 
 
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Location

 

Department of Aeronautics, Room 219City and Guilds BuildingSouth Kensington Campus

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Summary

 

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

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, ISSN:0140-0118

Lino M, Fotiadis S, Bharath AA, et al., 2022, Multi-scale rotation-equivariant graph neural networks for unsteady Eulerian fluid dynamics, Physics of Fluids, ISSN:1070-6631

Son O, Gao A, Gursul I, et al., 2022, Leading-edge vortex dynamics on plunging airfoils and wings, Journal of Fluid Mechanics, Vol:940, ISSN:0022-1120, Pages:1-30

Conference

Lindblad D, Sherwin S, Cantwell C, et al., 2022, Aeroacoustic analysis of a subsonic jet using the discontinuous Galerkin method, 28th AIAA/CEAS Aeroacoustics 2022 Conference, American Institute of Aeronautics and Astronautics, Pages:1-21

Lino M, Fotiadis S, Bharath AA, et al., Towards fast simulation of environmental fluid mechanics with multi-scale graph neural networks, AI for Earth and Space Science, ICLR, Pages:1-11

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