Kimberley Lennon

Email: c1068077@hallam.shu.ac.uk
Research Centre: MERI
PhD Thesis Title: Application of Machine Learning for Improvements in Nuclear Fusion Diagnostics
Director of Studies: Robin Smith
Supervisors: Andrew Alderson and Chantal Shand (UKAEA)

SUMMARY

I work part time at UKAEA as a Senior Experimental Nuclear Physicist, where I manage the radiation lab, called the RADLab (radiological assay and detection lab).

RESEARCH

The project aims to utilise state-of-the-art machine learning techniques to improve radioisotope identification using Germanium detectors.

One avenue to be explored is using machine learning for Pulse Shape Discrimination (PSD), to reduce the Compton background in detectors, which impacts the lower energy region of a gamma-ray spectrum, especially in high background environments.

Following this, machine learning methods will be used to explore improving the neutron spectrum unfolding process, a crucial method in understanding plasma parameters in fusion devices. The current methods have issues and includes using an apriori (guess) neutron spectrum, which causes limitations. New algorithms have the potential to improve fusion diagnostics methods.