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Personal profile

Research interests

Andrew is currently involved in several areas of research applying computational modelling to important problems in medicine and industry. A primary interest is in building a complete in silico pipeline for simulating magnetic resonance imaging of cardiovascular physiology in order to optimise diagnostic protocols and provide prognostic decision support to clinicians.

  • Computational modelling of cardiovascular diseases
  • Optimisation of medical imaging
  • In silico design of imaging contrast agents
  • Scientific software development for finite element methods
  • Mixing in laminar flows
  • Flow instability in helical pipes
  • Poroelastic fluid mechanics

He is involved in the following projects:

GW4 Translational Biomedical Research Network 

 

Willing to supervise PhD

1. Combining machine learning with modelling to improve medical imaging in cardiology.

Education/Academic qualification

Biofluid Mechanics, Doctor of Philosophy, Imperial College London

Fingerprint Dive into the research topics where Andrew Cookson is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Mechanics Medicine & Life Sciences
Heart-Assist Devices Medicine & Life Sciences
Cardiac Mathematics
Shear stress Engineering & Materials Science
Parameterization Engineering & Materials Science
Perfusion Medicine & Life Sciences
Heart Ventricles Medicine & Life Sciences
Physics Medicine & Life Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2015 2018

Research Output 2009 2019

A computational model to predict the onset of secondary flows of blood in a cone & plate rheometer

Kelly, N., Jelliffe, D., Gill, H., Fraser, K. & Cookson, A., 12 Jun 2019, (Accepted/In press).

Research output: Contribution to conferenceAbstract

13 Downloads (Pure)

Efficiently Generating Mixing by Combining Differing Small Amplitude Helical Geometries

Cookson, A., Doorly, D. & Sherwin, S., 1 Jun 2019, In : Fluids. 4, 2, p. 59-84 26 p., 4020059.

Research output: Contribution to journalArticle

Open Access
File
2 Citations (Scopus)
49 Downloads (Pure)
Open Access
File
Heart-Assist Devices
Hydrodynamics
Dynamic analysis
Computational fluid dynamics
Shear stress