I successfully defended my PhD research at my viva on 8 April 2020. My thesis was titled "Non-Invasive Assessment of the Aortic Pressure Wave: Development and Testing Using In Silico and In Vivo Data".
In my PhD I developed and tested a novel approach to calculate the central blood pressure (cBP) wave non-invasively from medical imaging data and a non-invasive peripheral pressure measurement, using zero and one- dimensional computational models of aortic haemodynamics (Am J Phys, 2021, 2018 World Congress of Biomechanics). This study included the development and testing of a range of tools to measure cardiovascular properties that are required to reconstruct the cBP wave from non-invasive clinical measurements. Moreover, I investigated the individual cardiovascular determinants of aortic pressure gradients. In all these projects I used both in silico and clinical datasets for algorithm development, testing, and validation. I also collaborated with PHILIPS Healthcare to incorporate my cBP algorithms within their prototype clinical MRI software (see MIUA 2016 and AHA 2017).


I started working on arterial blood flow models as a final year student in the Department of Aeronautics at Imperial College London. My MEng thesis is available here. During my MRes in the Department of Biomedical Engineering, King's College London, I performed a sensitivity analysis on a 1-D model of the human aorta to understand how model parameters influence the estimation of the aortic blood pressure (main results: Figure 1 and Figure 2). My MRes thesis is available here.

As part of my PhD, I have developed the following computational tools (available on request):

• a 0-D and 1-D model generator of populations of virtual subjects;
• a framework to determine optimum haemodynamic parameter estimation methods;
• a script to generate plots for the comparison of estimation and reference blood pressure waveforms;
• and a script to generate scatter and Bland-Altman plots for assessing the accuracy of blood pressure estimations.