Keywords
Fields of Research (FoR)
Biomedical engineering, Computational neuroscience (incl. mathematical neuroscience and theoretical neuroscience), Computational physiology, Biomechanics, Modelling and simulation, Cardiology (incl. cardiovascular diseases), Biological mathematicsSEO tags
Biography
Socrates Dokos is Associate Professor & Deputy Head of the Graduate School of Biomedical Engineering, UNSW Sydney, where his research interests lie in computational modelling of electrical and mechanical properties of excitable tissues, having published over 160 journal articles, book chapters and conference proceedings in this field. He has also published a sole-authored text on "Modelling Organs, Tissues, Cells and Devices". His research has...view more
Publications
ORCID as entered in ROS
https://orcid.org/0000-0002-7399-2712
Research Activities
Electric potential profile generated by retinal implant 98-electrode array
2D simplified computational model of cardiac contraction with mitral valve leaflet motion.
Simulated brain activation during electroconvulsive therapy.
2D simplified computational model of cardiac contraction with mitral valve leaflet motion.
Simulated brain activation during electroconvulsive therapy.
Anatomically-accurate model of rabbit cardiac pacemaker tissue defined using the MML framework, illustrating a propagating electrical wavefront emanating from the central pacemaking site.
Simulated brain activation during electroconvulsive therapy.
Anatomically-accurate model of rabbit cardiac pacemaker tissue defined using the MML framework, illustrating a propagating electrical wavefront emanating from the central pacemaking site.
Biological systems models typically contain many parameters, many of which are hidden and cannot be determined experimentally in the same system. We have developed custom methods for large-scale parameter optimisation of ionic cell models against electrophysiological data recorded in our laboratories.
Anatomically-accurate model of rabbit cardiac pacemaker tissue defined using the MML framework, illustrating a propagating electrical wavefront emanating from the central pacemaking site.
Biological systems models typically contain many parameters, many of which are hidden and cannot be determined experimentally in the same system. We have developed custom methods for large-scale parameter optimisation of ionic cell models against electrophysiological data recorded in our laboratories.
Simplified fluid-structure interaction model of ventricular assist flow in the presence of contracting heart wall and aortic valve leaflets. Ventricular inlet (left) and outlet (right) boundaries are shown as white squares, and ventricular assist flow occurs through the outlet at the bottom.
Biological systems models typically contain many parameters, many of which are hidden and cannot be determined experimentally in the same system. We have developed custom methods for large-scale parameter optimisation of ionic cell models against electrophysiological data recorded in our laboratories.
Simplified fluid-structure interaction model of ventricular assist flow in the presence of contracting heart wall and aortic valve leaflets. Ventricular inlet (left) and outlet (right) boundaries are shown as white squares, and ventricular assist flow occurs through the outlet at the bottom.
Electric potential profile generated by retinal implant 98-electrode array
Simplified fluid-structure interaction model of ventricular assist flow in the presence of contracting heart wall and aortic valve leaflets. Ventricular inlet (left) and outlet (right) boundaries are shown as white squares, and ventricular assist flow occurs through the outlet at the bottom.
Electric potential profile generated by retinal implant 98-electrode array
2D simplified computational model of cardiac contraction with mitral valve leaflet motion.