CV
Experience
Postdoctoral Researcher, ETH Zurich (Prof. Wallny group, CMS experiment) — 2022–present
Higgs physics (ttH, H→bb), generative ML for inference and calibration, E/Gamma reconstruction R&D. Creator and lead developer of PocketCoffea; heterogeneous PyTorch inference in CMSSW.
PhD Student, Università di Milano-Bicocca & CERN Doctoral Student Program — Oct 2018–Jan 2022
First evidence of semileptonic vector boson scattering; first GNN superclustering for the CMS ECAL; ECAL trigger optimisation.
CERN Technical Student, CMS experiment — 2016–2017
ECAL data-acquisition optimisation and monitoring tools during LHC Run 2.
Coordination roles
E/Gamma Physics Object Group Coordinator, CMS Collaboration — 2025–present
Co-lead of electron/photon reconstruction and calibration for the whole experiment; liaison to physics analysis groups.
ML Software Coordinator (L3), CMS Offline & Computing — 2022–2025
Integration and validation of ML models in CMSSW; ONNXRuntime and PyTorch C++ inference on CPU/GPU for HLT and offline reconstruction.
Education
MSc in Particle Physics, Università di Milano-Bicocca — 2016–2018, 110 cum laude
BSc in Physics, Università di Milano-Bicocca — 2013–2016, 110 cum laude
Technical skills
- Machine learning: graph neural networks, transformers, generative models (normalizing flows, flow matching), differentiable programming.
- Statistics: hypothesis testing (CLs), maximum likelihood estimation, unfolding, systematic uncertainty profiling.
- Languages: Python, C++, CUDA, ROOT (RooFit/RooStats).
- Libraries: PyTorch, TensorFlow, Scikit-HEP, Coffea, Pandas, Dask, SciPy, ONNXRuntime.
- Computing: Git, Docker/Apptainer, Linux, HPC clusters (HTCondor, Dask, GPU), CI/CD (GitLab, GitHub Actions), agent-based development and prototyping with LLM coding agents.