DrAidan Crilly

I am an Imperial College Research Fellow. My research is focused on the theory and numerical modelling of the observable signals in high energy density plasma and inertial confinement fusion experiments. The physics areas of particular interest to me are: neutron and radiation transport, diagnostic techniques, hydrodynamics and the properties of non-ideal plasmas. I am also interested in the application of AI/ML techniques in plasma physics, particularly in the inference process. These include Differentiable Programming, Markov Chain Monte Carlo, Gaussian Processes and Neural Networks.

I am also the deputy head of the 1st year undergraduate computing course which teaches students the basics of Python and its use in scientific computing. I also lecture a short post-graduate Machine Learning course in the Plasma Group (Slides & Code here).

PhD Thesis (Spiral)

My open source projects:

Neutron spectroscopy Python code - NeSST

Calculates primary and scattered neutron spectra for analyzing ICF experimental data.
Optical Thomson scattering spectra PythonJAX code - OTSax

Utilising differentiable programming to allow gradient descent methods for efficient fitting of experimental OTS data for non-Maxwellian ion distributions.
UROP open source projects:

1D electromagnetic particle-in-cell code in JAX by Sean Lim - PiC-Code-Jax