Computational Simulation
Development of mathematical and computational models for complex biological, physical and engineering systems.
Consulting service
Scientific Computing
I help organisations develop computational models, simulation tools and scientific software to understand, predict and optimise complex systems.
02
The opportunity
Turning scientific
knowledge into
engineering value.
Many engineering and scientific challenges cannot be solved through experimentation alone. Computational models and simulation provide a way to explore complex systems, evaluate hypotheses and support better decisions.
My PhD research in computational modelling provides a strong foundation for scientific computing applications across medical technology, life sciences and computational R&D, including in silico modelling, simulation and computational medicine.
- Computational modelling of physical and biological systems
- Numerical methods and simulation workflows
- Parameter estimation and uncertainty quantification
- Sensitivity analysis and optimisation
- Scientific software engineering
How I can help
Capabilities
Model Calibration & Optimisation
Parameter estimation, sensitivity analysis and uncertainty quantification for computational models using data-driven approaches.
From Research to Production
Transforming computational prototypes into reliable, maintainable software systems suitable for real-world use.
Selected experience
Project portfolio
Computational Cardiac Modelling
Mathematical modelling and numerical simulation of cardiac electrophysiology to study electrical propagation and understand mechanisms underlying cardiac behaviour.
Biomechanical Modelling of Lung Motion
Development of patient-specific computational models to simulate organ deformation and support improved understanding of biological motion.
Parameter Estimation & Uncertainty Analysis
Development of computational approaches for estimating model parameters and analysing uncertainty in complex multiparameter systems.
Satellite & Sensor Data Analytics
Applying computational methods, machine learning and signal processing to extract insights from complex real-world data.
Application areas
Where scientific computing
creates impact.
- Medical technology and computational medicine
- Life sciences and in silico modelling
- Industrial simulation and digital twins
- Earth observation and environmental modelling
- Research and engineering applications
Start a conversation