Research programme
The work is organised by physical dependency rather than by PhD or postdoctoral stage. Fundamental scattering models feed transport simulations; geometry and uncertainty make those simulations credible; radiation-material studies turn them into design insight.
Scientific pathway
Each stage supplies assumptions, geometry, or data to the next. This is why the research is presented as one continuous body of work.
Elastic cross sections and dielectric energy-loss functions.
Monte Carlo trajectories, emission, and primary-knock-on events.
Experimental morphology translated into simulation-ready meshes.
Model-form and statistical confidence evaluated systematically.
Damage and defect evolution connected to microstructure.
Research areas
The same computational methods recur across semiconductor metrology, radiation damage, scientific software, and data-driven analysis.
Monte Carlo models of how electrons and ions travel, scatter, and deposit energy inside solids, with uncertainty quantified alongside the prediction.
Modelling collision cascades, primary damage, and defect evolution to understand how alloys survive irradiation in nuclear, fusion, and space environments.
Simulation, meshing, and coupling workflows in C++, Fortran, Python, and MPI for complex three-dimensional material geometries.
Manifold learning, Gaussian-process kernels, denoising, and surrogate methods used to analyse scientific data and reduce simulation cost.
The enabling stack includes Monte Carlo simulation, C++ and Fortran physics libraries, Python analysis, MPI campaigns, Gmsh geometry, IM3D, CRT, and MMonCa.