Objective
The discovery of the Higgs boson was a landmark achievement in particle physics, but many fundamental questions remain unanswered, especially how the Higgs boson interacts with itself. Measuring this self-interaction will reveal how the Higgs field shaped the early Universe and why matter exists in abundance over antimatter. Deviations from expected values could shed light on the origin of dark matter and cosmic inflation. This project focuses on the most sensitive way to study this: the simultaneous production of two Higgs bosons (“di-Higgs” production).
Observing di-Higgs production is extremely challenging due to its rarity and the complexity of its experimental signatures. The High-Luminosity Large Hadron Collider (HL-LHC) will soon deliver the only dataset capable of probing the Higgs self-coupling for the foreseeable future, yet current reconstruction methods may fall short. At the same time, machine learning has entered a new era: transformer and segmentation models, already revolutionising natural language processing and medical imaging, are now ready to transform collider physics. The convergence of these developments creates a unique opportunity, which I am ideally positioned to seize.
I have pioneered the use of graph neural networks and transformers in ATLAS, spearheaded flavour tagging innovations, and led Higgs analyses. This rare combination of expertise, spanning reconstruction, machine learning, and Higgs physics, equips me to lead a conceptual leap.
UNMASK will re-imagine the core reconstruction tasks of charged particle tracking and b-jet identification as holistic segmentation problems, inspired by state-of-the-art architectures from computer vision such as MaskFormer. By overcoming the limits of today’s modular algorithms, it will unlock unprecedented sensitivity to di-Higgs production, while delivering broadly applicable tools for the HL-LHC and future colliders, establishing a new paradigm for reconstruction in particle physics.
Fields of science (EuroSciVoc)
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2026-STG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
3526 KV Utrecht
Netherlands
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.