CV

This is a brief summary of my education and research experiences, for further information please contact me via email.

Education

• PhD in Particle Physics, Imperial College London (2023–Feb. 2027)
  • PhD Thesis: “Exploring fundamental physics interactions through spin correlations in tau lepton pairs”, supervised by Prof. David Colling
  • Long-term placement at CERN (2024–2025).
• Master in Physics (MSci), Imperial College London (2019-2023)
  • First Class Honours, average of 79.5% (top 5% of the cohort)
  • Master’s Thesis: “Identification of hadronic tau lepton decays with domain adaptation using adversarial machine learning techniques at CMS”, supervised by Dr Konstantin Androsov (awarded 90%).
  • Exchange year at École Polytechnique Fédérale de Lausanne (2021–2022), average of 5.67/6.
• French Baccalaureate, Lycée Francais Charles de Gaulle (2012-2019)
  • Scientific stream, specialisation in Mathematics, Highest honours (Mention Très Bien), overall grade of 20.11/20.

Research Experience

• Analysis of the CP structure of the tau lepton Yukawa coupling at CMS (2023–2026)
  • Main analyser and contact person for the early Run 3 measurement of the CP nature of the Higgs boson coupling to tau leptons, accepted by JHEP (arXiv:2606.03510). Presented the result for the first time in a plenary talk at Moriond QCD.
  • Built a new columnar analysis framework (with coffea), improved analysis sensitivity with optimised event selections and classification, and performed the statistical inference and interpretation of results.
  • Achieved world-leading sensitivity, with a better expected exclusion of the CP-odd scenario than the previous CMS result, despite using less than half the amount of data (65% increase accounting for reduced luminosity).
• Identification of hadronic tau lepton decays with domain adaptation at CMS (2022–2025)
  • Core developer of DeepTauv2p5, the convolutional neural network which is the default tau identification algorithm for early Run 3 CMS analyses, published in JINST (arXiv:2511.05468).
  • Introduced domain adaptation to reduce the impact of mismodelling in simulation, and achieved a reduction of 40% in the jet misidentification rate compared with previous methods.
  • Measured efficiency and energy scale corrections used by all early Run 3 analyses involving taus.
• Determining tau lepton spin properties using conditional normalising flows (2026)
  • Developed a new method to determine tau polarimetric vectors (most likely direction of the tau spin), estimating the undetected neutrino momenta using a conditional normalising flow, submitted to Phys. Rev. D (arXiv:2608.10961).
  • Reconstructed the polarimetric vector in all major tau decay topologies for the first time, demonstrating overall H→ττ CP sensitivity gains of 18% (up to 88% in some final states) on simulated LHC data. Enables further applications including spin-based background suppression and entanglement measurements.
• Muon Cooling at the J-PARC g-2 Experiment, KEK Tsukuba (Summer Student, Summer 2023)
  • Designed and built an external cavity diode laser, and simulated beam tolerance to misalignment in Geant4.

Positions of Responsibility

• Convener of the CMS Tau Algorithms Subgroup (L3) (2025–Present)
  • Coordinating a team of ∼10 people working on tau lepton reconstruction and identification algorithms.
  • Oversaw the release of several public documents, including a paper (JINST 20 (2025) P12032) and three detector performance notes: CMS-DP-2025-047, CMS-DP-2025-073, CMS-DP-2025-074.
• Monte Carlo Contact for the CMS Tau Physics Object Group (2024–Present)
  • Coordinating the production of simulated samples needed for central corrections and new developments.
  • Identified significant mismodelling of tau leptons in central CMS simulations affecting Madgraph/aMC@NLO and Pythia, proposed and validated a fix, leading to the successful reproduction of over 30 billion events, benefiting all Run 3 analyses involving tau leptons.
• CMS Technical Shifter (2025)
  • Ensured good detector operations and safety across the CMS site during LHC data-taking.

Selected Publications

A full list of publications is available on INSPIRE-HEP.

• [1] CMS Collaboration, “Analysis of the CP structure of the Yukawa coupling between the Higgs boson and tau leptons in proton-proton collisions at √s = 13.6 TeV”, arXiv:2606.03510 [hep-ex], accepted by JHEP (2026).
• [2] CMS Collaboration, “Identification of tau leptons using a convolutional neural network with domain adaptation”, JINST 20 (2025) P12032.
• [3] D. Winterbottom and L. Russell, “TauPolaris: reconstructing tau lepton polarimetric vectors with conditional normalizing flows”, arXiv:2608.10961 [hep-ph], submitted to Phys. Rev. D (2026).

Conference Talks

• Plenary talk at Rencontres de Moriond QCD, “Higgs CP studies and other Higgs properties at ATLAS and CMS”, La Thuile, Italy (2026). Proceedings: arXiv:2606.05897.
• Parallel talk at the Institute of Physics HEPP/APP Conference, “Analysis of the CP structure of the Higgs-tau Yukawa coupling at CMS”, Edinburgh, UK (2026).
• Topical plenary talk at Higgs Hunting, “Measurement of the CP structure of the Higgs boson to tau lepton Yukawa coupling at CMS”, Paris, France (2026, upcoming).

Awards

• Schrödinger PhD Scholarship — Outstanding academic performance and research potential (2023–2027)
• Dean’s List — Top 10% of the cohort in Years 3 and 4 (2022–2023)
• Ken Allen Prize — For academic excellence (2022)

Teaching and Outreach

• Graduate Teaching Assistant / Assessor, Imperial College London (2023–Present)
  • Teaching assistant and assessor for Computational Physics, Mechanics and Relativity, Data Science and Machine Learning, Advanced Particle Physics, and Applied Data Science.
  • Supervision of undergraduate summer projects.
• Outreach (2023–Present)
  • Introductory Standard Model lecture to 100+ high school students; CMS outreach video at Moriond QCD (40k+ views); public engagement at Imperial’s Exhibition Road Festival; and CMS underground tour guide.

Additional Skills and Interests

• Programming: Python, C++ (including ROOT), Linux (Bash/Zsh), LaTeX, Git.
• HEP/ML Tools: Machine learning (PyTorch, TensorFlow), columnar analysis (coffea), statistical inference (Combine), MC generators (Madgraph/aMC@NLO, Powheg, Pythia), Geant4, CMSSW.
• Languages: Native in English and French, intermediate in Spanish.
• Personal Interests: Cycling, running, football, skiing, piano.