Aidan Crilly

Aidan Crilly is an Eric and Wendy Schmidt AI in Science Postdoctoral Fellow at Imperial College London's Department of Physics (Faculty of Natural Sciences). He holds affiliations with the MAGPIE, Minotaur, NeSST, and OTSax research groups. His work focuses on theoretical and numerical modeling of observable signals in high-energy-density plasma experiments, particularly neutron spectroscopy, radiation transport, and non-ideal plasma properties. He applies AI/ML techniques like differentiable programming, Gaussian Processes, and neural networks to plasma diagnostics. Crilly teaches as deputy head of the 1st-year undergraduate computing course (Python for scientific computing) and lectures a postgraduate Machine Learning course in the Plasma Group.

Research Interests:

• Plasma diagnostics and hydrodynamics
• Neutron scattering spectroscopy
• Optical Thomson scattering analysis using JAX
• Machine learning for plasma inference
• Non-Maxwellian ion distribution fitting

Projects: Developed open-source tools including NeSST (neutron spectrum analysis), OTSax (differentiable Thomson scattering), and PiC-Code-Jax (electromagnetic PIC simulations). Active in Imperial's AI Network and contributes to the Spiral PhD research program.

Awards: Recipient of the Schmidt Futures AI in Science postdoctoral fellowship.