IRIS-HEP Fellow: Jason Wong

Fellowship dates: May – Aug, 2021

Home Institution: University of California, Berkeley

Project: Developing Lorentz Equivariant Graph Neural Networks for Top Quark Tagging

Top quark tagging is the process of labeling quarks and gluons from particle accelerator data. Machine learning helps automate this labeling process to help us understand physics and test theories. The goal of this project is to use graph neural networks to improve the accuracy of the labeling process and also imposing Lorentz symmetry into the network architecture to greatly reduce the training time.

More information: My project proposal

  • Savannah Thais (Princeton University)
  • Daniel Murnane (Lawrence Berkeley National Laboratory)

Presentations and Publications
Current Status

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