✍️Daniel Murnane
DDSA Postdoctoral Fellow
I am currently a postdoctoral fellow at the Niels Bohr Institute, University of Copenhagen. I am funded by the Danish Data Science Academy, pursuing a research programme focused on “Physics Language Models” - a new paradigm for understanding and generating high energy physics behaviour with geometric machine learning.
Experience
DDSA Postdoctoral Fellow
Niels Bohr Institute, University of CopenhagenResearch Affiliate
Lawrence Berkeley National LaboratoryMachine Learning Co-convener
ATLAS CollaborationPostdoctoral Researcher
Lawrence Berkeley National Laboratory
Education
PhD Particle and Astrophysics
University of AdelaidePhD Thesis titled The Landscape of Composite Higgs Models . Supervised by Prof Anthony G Williams and Prof Martin White.Read ThesisBSci in High Performance Computational Physics, with First Class Honors
University of AdelaideHonors Thesis titled What’s the Matter: Supersymmetric Dark Matter Searches with CMS Data. Supervised by Prof Anthony G Williams and Prof Martin White.
Publications
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Graph neural networks for particle reconstruction in high energy physics detectors (2020)
Apr 23, 2024
Hierarchical Graph Neural Network
Apr 23, 2024
Influencer Loss: End-to-end Geometric Representation Learning for Track Reconstruction
Apr 23, 2024
A Language Model for Particle Tracking
Jan 1, 2024
Graph Neural Networks for track reconstruction in the ATLAS ITk detector at the Large Hadon Collider
Jan 1, 2024