Talks & Teaching

Conference talks

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
Track convener, “Offline Computing”, CHEP 2024 — scientific committee, review and selection of contributions.
PocketCoffea tutorials — PyHEP 2023 (with M. Marchegiani) and PyHEP.dev 2024.

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.

Supervised 3 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.