The Computational Cardiovascular Science Team

The Computational Cardiovascular Science group is an interdisciplinary team of scientists aiming at translating their background in Engineering, Mathematics, Physics, and Biology to Cardiovascular Research. Each of our teammates has a different range of skill sets and we enjoy combining them to contribute to improving the understanding of the human hearts in health and disease, and to develop new mathematical and computational methodologies for Cardioascular Research.

Visit also our Former Members section.

NamePictureAreas of InterestContact
Blanca Rodriguez

Wellcome Trust Senior Research Fellow in Basic Biomedical Sciences

Professor of Computational Medicine

Principal investigator within the BHF CRE
Blanca Rodriguez
Computational Cardiac Electrophysiology

Mechanisms determining variability in the response of the human heart to anti-arrhythmic therapy in acute myocardial ischaemia, hypertrophic cardiomyopathy and atrial fibrillation.
Blanca's profile
Vicente Grau

Professor of Biomedical Image Analysis

Director of Centre for Doctoral Training in Healthcare Innovation
Biomedical image analysis

Development of novel algorithms for biomedical image analysis in combination with computational models, and their application in cardiovascular and pulmonary medicine.
Vicente's profile
Alfonso Bueno-Orovio

British Heart Foundation Intermediate Basic Science Research Fellow

Associate Professor of Computational Medicine

Principal investigator within the BHF CRE

Integrative approaches for Cardiovascular Research

Interplay between cardiac function and structure in modulating deadly arrhythmias in the human heart, computer modelling and simulation towards a reduction and replacement of animals in research and safer drugs in human, and advanced mathematical modelling for cardiac tissue and magnetic resonance imaging.
Alfonso's profile
Kevin Burrage

Visiting Professor, 2016-2019.

Professor of Computational Mathematics, QUT, Brisbane, Australia

Development of novel modelling and simulation approaches in Computational Biology

To capture the underlying variability in dynamical processes and to characterise the heterogeneity in biological tissues through stochastic and nonlocal multiscale techniques.
Kevin's profile
Yoram Rudy

Visiting Professor of Computational Medicine, Washington University in St. Louis
Yoram Rudi
Cardiac Bioelectricity, Electrophysiology and Arrhythmias, Computational Biology and Modeling of the Heart, Cardiac Electrical Imaging and Mapping

Understanding the mechanisms that underlie normal and abnormal rhythms of the heart at various scales, from the molecular and cellular to the whole organ. The development of novel non-invasive imaging modalities (Electrocardiographic Imaging, ECGI) for the diagnosis and guided therapy of cardiac arrhythmias.
Yoram's Profile
Elisa Passini

Senior Postdoctoral Researcher
Elisa Passini
Computational modelling and simulation in Safety Pharmacology
Human in silico drug testing for the prediction of safety and efficacy of drug action in human.
Elisa's profile
Xin Zhou

Senior Research Associate
The development and use of mathematical models of human ventricular cell electrophysiology 

To investigate the effect of variability in the generation of potential pro-arrhythmic conditions in human ventricles. Especially, the modelling of the ionic mechanisms underlying excitation-contraction coupling, genetic disorders in ion channels, and drug response in human.

Xin's profile
Linford Briant

Sir Henry Wellcome Postdoctoral Fellow
Linford B
Mechanisms regulating glucagon secretion from pancreatic alpha-cells Linford's profile
Zhinuo (Jenny) Wang

Postdoctoral Researcher

Modeling heart electrophysiology and arrhythmia risk stratification in hypertrophic cardiomyopathy 

Developing 3D computational models of the heart to investigate the effect of hypertrophic-related heterogeneities in the electrical properties of the myocardium on its susceptibility to arrhythmia. 

Jenny's profile
Lei Wang

Postdoctoral Researcher

Electromechanical modelling of the heart 

Develop fast computational toolkits to reproduce the heart structure and function, including ionic dynamics and activation (electrophysiology), contraction and pump blood (mechanics) and scar growth and remodelling (biochemistry), and search key mechanisms in myocardial infarction (MI), aiming to aid clinical management and drug development for MI. 

Lei's profile

Aditi Roy

Postdoctoral Researcher

 Aditi Roy Computational modelling and simulations in Atrial Fibrillation

Development of multiscale computer models of human atrial electrophysiology, built through the integration of multimodality datasets. Investigate variability in atrial fibrillation mechanisms through computer simulation studies using populations of models, informed by clinical datasets. 

Aditi's profile

Rubén Doste

Postdoctoral Researcher

Ruben Doste

Computational modelling and simulation in Hypertrophic Cardiomyopathy

Development of personalised human ventricular models and conduction of high performance computing studies to investigate risk stratification and tailoring of pharmacological therapy in human hypertrophic cardiomyopathy.

Ruben's profile
Karen Barnes

PA to Prof Blanca Rodriguez
Karen Barnes
Personal Assistant to Prof Blanca Rodriguez Karen's profile
Jakub Tomek

Postdoctoral Researcher
 Jakub Tomek

Interdisciplinary investigation of cardiac function

Using a combination of detailed human-based computational modelling with wet-lab experiments and data analysis to understand the mechanisms underlying cardiac [dys]function, with focus on arrhythmogenesis.

Cristian Trovato

DPhil in Computer Science, 2016-2019
Cristian Trovato
 Drug effects on the cardiac Purkinje system Cristian's profile
Peter Marinov

DPhil in Computer Science, 2016-2019
Peter Marinov
A modelling and ECGi approach to Arrhythmogenic Right Ventricular Cardiomyopathy Peter's profile
Julià Camps

DPhil in Computer Science, 2017-2020

Machine learning for ECG signals Julia's profile
Beth McMillan

DPhil in Computer Science, 2015-2018


Predicting drug-induced Torsades de Pointes arrhythmias


Beth's profile
Francesca Margara

Marie Curie DPhil Fellow, 2018-2021

Personalised analysis of drug safety and efficacy

Personalised models of human cardiac electromechanical physiology to predict the safety and efficacy of pharmacological action in the individual subject.

Francesca's profile
Hao Xu

DPhil in Computer Science, 2015-2019

Hao Xu
Biomedical Image Analysis

Automated segmentation of Cardiac MRI scans based on deep learning. Anatomical and functional analysis of left ventricle.

Hao's profile
Jorge Corral Acero

Marie Curie DPhill Fellow, 2018-2021

Cardiomyopathy under the lenses of cardiac MRI & computer models

Synergies of cardiac MRI and computer models to address hypertrophic cardiomyopathy: CMR analysis, based on deep learning approaches and combination of ML techniques and personalised models.

Jorge's profile
James Coleman

DPhil in Computer Science 2020-2023
 James Coleman Mechanistic investigations of structural-functional interplay as causal mechanisms of arrhythmic risk in hypertrophic cardiomyopathy

Development of human multiscale biventricular bidomain models of HCM patients to include patient-specific ischemic and fibrotic burdens, to stratify arrhythmic risk.

James' profile
Hannah Smith

DPhil in Computer Science 2019-2023
Hannah Smith

Computational investigation into the interplay between pro-arrhythmic and mechanical abnormalities

Investigating population variability in cardiac excitation-contraction coupling to improve drug safety profiling and arrhythmic risk stratification'. My DPhil is technically in 'Ion Channels and Disease'.

Hanna's profile
Luana Riebel

DPhil in Computer Science 2020-2023
Luana Riebel

My main research interest is how we can use computer simulation to provide a more ethical, accurate, faster and cheaper representation of biomedical processes. In my final year of my Master's degree I was part of a group research project aiming to predicting alarm validity by using machine learning on ECG signals, which sparked my interest in cardiovascular science. 

Luana's profile
Max Cumberland

BHF/NC3Rs PhD student at the Institute of Cardiovascular Sciences, University of Birmingham
Max Cumberland

Use of induced pluripotent stem cell derived cardiomyocytes to test the consequences of genetic variants in atrial and ventricular arrhythmias

Using iPSC-CM cellular systems and computational modelling to investigate the impact truncating variants in the gene titin have on atrial fibrillation and ventricular arrhythmias


 Max's profile
Albert Dasí i Martinez
Marie Curie DPhil Fellow, 2020-2023 

Atrial state characterization and treatment improvement in the context of atrial fibrillation 

Brief description: To deliver new technologies and novel strategies for individualized characterization of atrial fibrillation substrate to and increase treatments’ efficiency.

Ambre Bertrand
DPhil in Computer Science (EPSRC CDT in Health Data Science), 2021-2025 

Dissecting disease heterogeneity in heart failure patients using multi-modal machine learning, modelling, and simulation methods.

Ambre's profile