Bio
As a member of the ATLAS collaboration, the largest experiment in CERN's Large Hadron Collider complex, my research interests lie in searching for the fundamental ingredients of the universe beyond our “Standard Model” of particle physics (SM). As an AI in Science Fellow, my project is to develop Graph Neural Networks for improved collision classification, building on previous work using the relationships between collision events to define graph-based variables able to discriminate between events where Beyond-SM particles were made and where only SM particles were produced. I am also co-leader of the Leptons+X Exotics physics subgroup, helping to lead part of the BSM search program in ATLAS focused on topics including things like lepton flavour violation, leptoquarks, extra dimensions, heavy neutral leptons, and composite/vector-like lepton models. Finally within ATLAS I am an expert in the detector signature for dark matter - missing transverse momentum - and involved in designing new calibration and Machine learning techniques to improve its accuracy, precision and modelling, both at reconstruction and Trigger level.
I am part of the European Committee for Future Accelerator's Early-Career Researcher panel, advocating for ECR views in the decision-making process for future colliders.
Prior to this I was a Research Fellow at Peterhouse, Cambridge, primarily improving our detector signature for invisible particles like Dark Matter, through the measurement of “missing transverse momentum” both at Trigger and Reconstruction levels, after completing my PhD and MSci in Physics at King’s College, Cambridge. During my PhD I searched for supersymmetry, leptoquarks, and unexpected lepton charge-flavour asymmetries hiding within our collision data.