Edoardo Critelli

I'm originally from Italy and hold an MSc in Particle Physics from I joined the UCL CDT in Data Intensive Science drawn by its unique environment that blends cutting-edge research in particle physics.

Project title: Graph Neural Networks for High Energy Physics

Research Group: High Energy Physics

Supervisor(s): Dr Gabriel Facini

Introduction: 

I'm originally from Italy and hold an MSc in Particle Physics from Sapienza Roma. My Bachelor's and Master's theses were completed with the CMS collaboration at CERN, focusing on the discovery of the Higgs Boson and the precision measurement of the Z boson cross-section. Afterwards, I gained several years of experience as a big data engineer, working with global clients in Media and Fintech on data analytics and anti-money laundering projects.

I was attracted to the UCL CDT in Data Intensive Science by its unique environment, which combines cutting-edge research in particle physics, the latest advancements in Machine Learning and AI, and a strong emphasis on industry collaboration. At the CDT, I will focus on flavour identification via graph neural networks of hadronic jets and tracking optimisation using Graph Neural Networks at the ATLAS collaboration at CERN, under the supervision of Dr. Gabriel Facini and Prof. Tim Scanlon.

I am incredibly excited about my time at the CDT and eager to contribute to the research program of the UCL Group and the Atlas collaboration at CERN!

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Project description:  

In my project, I will be working with the ATLAS Collaboration at the Large Hadron Collider (LHC) at CERN to develop novel and improve existing tracking and flavour tagging methods used by ATLAS to classify events produced in the LHC, using Machine Learning techniques and Graph Neural Networks. The UCL Group has pioneered the usage of graph neural networks and transformers for the identification of b-hadrons, developing the transformer-based models GN2 and GN2X, and I will contribute to their improvement, extension, optimisation and to the development of the next generation of taggers.

The main application in physics analysis will be in the Higgs sector, to perform precision measurements of the Higgs boson with a main focus on its decay to b-hadrons, especially in the boosted regime.

First year group project: Peak.ai

Placement: 

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