Particle physics DPhil student in the Exotics Group
Research Interests
HHH production
I conducted the first ever search for the triple Higgs boson(HHH) production at the LHC in the 6b final state. The SM HHH production directly probes the quartic Higgs self-coupling, which sheds light on the nature of electroweak symmetry breaking and the stability of the Universe. As a principal analyser, I led the development of a machine learning algorithm to separate signal from background, as well as the optimisation of trigger strategy and background modelling. The search produced one of the landmarks results of the ATLAS experiment in 2024, and I presented them on behalf of the team at the Higgs2024.
ATLAS b-jet triggers
As an active member of the ATLAS b-jet trigger group, contributing to algorithmic development, calibration and operation during ATLAS data-taking. I developed a machine learning algorithm to reject jets arising from g->bb splitting, a common background in the LHC, and presented it at ICHEP 2022 and LHCP 2023.
ML for particle physics
I have a strong interest in the development of machine learning techniques for high energy physics. My projects include kinematic regression using Deep Sets networks and a novel approach using dataset-wide Graph Neural Networks to search for exotic physics signatures.