Talks & Teaching
Conference talks
- From bins to flows: a neural network approach to unbinned data-simulation corrections for CMS — parallel talk, ICHEP 2026
- From bins to flows: a neural network approach to unbinned data-simulation corrections — ACAT 2025 (poster)
- Efficient data movement for Machine Learning inference in heterogeneous CMS software — FastML 2025 (poster); also at ACAT 2025 with C. Zeh, L. Michalski, L. Beltrame, F. Pantaleo, E. Cano. Zero-copy SoA→PyTorch tensors with Alpaka for GPU inference in CMSSW.
- ML in Higgs Physics — plenary talk, Higgs 2024
- Higgs / Top / EWK and combined EFT results at CMS — parallel talk, LHCP 2023
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Track convener, “Offline Computing”, CHEP 2024 — scientific committee, review and selection of contributions.
- PocketCoffea tutorials — PyHEP 2023 (with M. Marchegiani) and PyHEP.dev 2024.
Invited seminars and lectures
- Uncertainties in ML — lecture, AIPHY2 school: Bayesian Statistics, Gran Sasso Science Institute, L’Aquila (Oct 2026)
- Lecturer, CERN STEAM Academy — summer school on software, edge computing and machine learning, CERN (Jul 2026)
- Machine Learning in CMS: New Approaches for High-Energy Physics Challenges — seminar, University of Warsaw (Nov 2025)
- Normalizing Flows in High-Energy Physics Applications — PhD course lecture, Purdue University (Nov 2025)
- Machine Learning in CMS: New Approaches for High-Energy Physics Challenges — seminar, University of Bristol (Nov 2024)
- Machine Learning tools for precision physics — PhD course, Milano-Bicocca (Oct 2024). Transformers and probability modeling for HEP.
Teaching and supervision
- Supervised 4 PhD students and 10+ BSc/MSc students at ETH Zurich.
- Teaching assistant, Statistical Methods and Analysis Techniques in Experimental Physics (MSc), ETH Zurich, 2025–2026.
- Teaching assistant, Physics Lab 1, ETH Zurich, 2022–2025.