Emanuele Usai
Assistant Professor Of Physics (tenure Track) at The University of Alabama
Tuscaloosa, Alabama, United States
Summary
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Rockstar🎓
Top SchoolEmanuele Usai is a data-driven physicist and assistant professor with 11 years of experience building large-scale physics analyses, machine learning models, and production data pipelines for high-energy experiments. He led a 15-person data quality team at CERN, delivering 98% certified high-quality data and 100% KPI attainment on a $500M detector, and scaled ML workflows to petabyte datasets while cutting training times 20× via TPU collaboration. Equally fluent in C++, Python, and domain-specific tooling, he has contributed Monte Carlo generator work to the CMS genproductions repo, enabling new-physics simulation studies. His research blends practical engineering—robotic sensor commissioning and software refactoring that improved compute by 30%—with novel algorithms for particle ID and anomaly detection that materially improved sensitivity. Based in Tuscaloosa, he combines academic publication impact and cross-functional leadership with a persistent focus on operational efficiency and reproducible open data.
11 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Elementary Particle Physics, Summa cum laude (with highest honors), Doctor of Philosophy - PhD, Elementary Particle Physics, Summa cum laude (with highest honors) at University of HamburgMaster's degree, Physics, Master's degree, Physics at Università degli Studi di Torino
English, Italian, German, French
Github Skills (11)
simulations10
simulation10
sh10
script10
shell10
physics10
python10
monte-carlo10
scripting10
modeling10
data-analysis8
Programming languages (7)
Github contributions (5)
cms-sw/genproductions
May 2015 - Jun 2018
Generator fragments for MC production
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits, 2 PRs, 11 comments in 3 years 1 month
Contributions summary:Emanuele contributed to the generation of Monte Carlo simulation gridpacks, primarily focused on adding and configuring models for new physics processes, specifically Z' -> VLQ and RSGluon to ttbar decays. They modified shell scripts for model integration and developed Python scripts to create configuration cards for MadGraph5_aMCatNLO. The contributions involve defining masses, widths, and other parameters within the simulation framework to generate different particle decay scenarios.
productionfragments
ML4SCI/MLMapper
Aug 2021 - Oct 2023
Contributions:4 PRs, 6 pushes, 1 branch in 2 years 2 months
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