Developing the first software-based neutral hadron tagger for the BESIII experiment using a transformer-based deep neural network on EMC and TOF signals. The trained model is exported to ONNX and integrated into a dedicated BOSS algorithm for event-by-event inference within the standard BESIII reconstruction chain. Continuing quantum machine learning research for future HEP applications.

Built quantum machine learning algorithms and studied their application in High Energy Physics. Led the first published application of QSVM to Higgs physics at the CEPC. Continued as corresponding analyst on the ATLAS heavy resonances publication.

Thesis research encompassed: the first ATLAS search for heavy resonances in the 4ℓ + MET/jets channel (analysis contact); non-resonant Higgs pair production in four leptons; off-shell Higgs production and total width in ZZ → 4ℓ; missing transverse energy performance for ATLAS authorship qualification; multi-lepton anomalies at the LHC; and Higgs differential cross-sections at the CEPC.

Research on the search for Higgs boson pair production in the WW*γγ channel at ATLAS, and the impact of additional BSM scalar bosons in explaining multi-lepton anomalies at the LHC. Concurrent Teaching Assistant in the School of Physics.

Thesis on the theory behind Dalitz plots and the use of the EvtGen event generator for B-meson decay simulation.

Studied classical mechanics, electromagnetism, quantum mechanics, thermodynamics, optics, and nuclear physics. Graduated with Honours.