My research interests are in the following areas:

Cardiovascular modelling and subject-specific analysis, medical device design and optimisation, reduced order and probabilistic modelling, forward and inverse uncertainty propagation, surrogate modelling, information theory, and inverse problems.


  1. Pant, S. Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems Journal of The Royal Society Interface 15 142 20170871
  2. Pant, S., Corsini, C., Baker, C., Hsia, T., Pennati, G., Vignon-Clementel, I. A lumped parameter model to study atrioventricular valve regurgitation in Stage 1 and changes across Stage 2 surgery in single ventricle patients IEEE Transactions on Biomedical Engineering 1 1
  3. Pant, S., Corsini, C., Baker, C., Hsia, T., Pennati, G., Vignon-Clementel, I. Inverse problems in reduced order models of cardiovascular haemodynamics: aspects of data assimilation and heart rate variability Journal of The Royal Society Interface 14 126 20160513
  4. Pant, S., Corsini, C., Baker, C., Hsia, T., Pennati, G., Vignon-Clementel, I. Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation Journal of Biomechanics 49 11 2162 2173
  5. Lombardi, D., Pant, S. Nonparametrick-nearest-neighbor entropy estimator Physical Review E 93 1

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  • EG-268 Experimental Studies - Mechanical

    The course introduces the students to experimental studies in a wide range of subjects. There are four individual experiments (HEAT/JET/STRESS/VIBRATION) Each experiment is self contained and the student will be assessed via either: ¿ A lab report which will have a set of experiment specific questions to answer. ¿ An online Blackboard assessment. All students work in groups and carry out four experiments, however the assessments are all individually submitted. The students keep a log-book of the experimental observations and results, which is used for reference for the technical report from each experiment written-up in the week after the experiment.

  • EG-362 Fluid Mechanics 3

    This module aims to generate ability to solve the problems and explain physical phenomena on the topic of fluid mechanics. The module will cover inviscid fluids, momentum and mass conservation in viscous fluids, boundary layer flows and compressible fluid flow. The module includes turbomachinery including pumps (centrifugal and axial) and turbines (impulse and reaction).

  • EGA265 Fluid Mechanics 2

    This module aims to build on the concepts taught on stationary and flowing fluids in EG-160 and extend the knowledge to solve the problems and explain physical phenomena that involves internal and external flows. The module will cover: (i) dimensional analysis and modelling; (ii) flow through piping networks and pump selection, flow rate and velocity measurement; (iii) prediction of lift and drag for flows over common geometries, (iv) fluid kinematics and preliminary differential analysis of fluid flow.


  • Aneurysm/stenosis detection through non-invasive peripheral measurements (current)

    Other supervisor: Prof Perumal Nithiarasu
  • Optimal Design for Inverse Problems in Biomedical Engineering (current)

    Other supervisor: Prof Perumal Nithiarasu

Awards And Prizes

Date Description
2014 Inria post-doctoral fellowship
2012 SET for Britain
2012 Overseas Research Awards Scheme
2010 Runners-up in Star CCM+ calendar (computational simulation) competition

Key Grants and Projects

  • Model2Decision ESPRC Network (principal investigator) 2017 - 2018

    Do self-expandable artificial valves offer an advantage over balloon-expandable valves in patients with calcified aortic roots? , £8,104

  • British Heart Foundation project grant (co-investigator) 2017 - 2020

    Large-scale validation of computer simulations for personalised cardiovascular treatments in congenital heart disease. Principal investigator: Dr. C. Capelli, University College London., £183,422

  • Life sciences bridging fund, Welsh government (co-investigator) 2017 - 2018

    Integrating reduced-order models in clinical decision support systems for non-invasive diag- nosis of coronary artery disease. Principal investigator: Prof. P. Nithiarasu, Swansea University. , £46,191