Luca Giommi
Tecnologo Di Ricerca at CERN
Bologna, Emilia-Romagna, Italy
Summary
👤
Senior🎓
Top SchoolLuca Giommi is a research technologist and Data Science PhD candidate with nine years of experience applying machine learning to high-energy physics and log analysis, currently based at INFN CNAF and a CMS collaborator at CERN. He combines strong physics training (110/110 con lode) with practical software engineering skills in Python, C++, ROOT and containerized cloud deployments, and has contributed backend improvements to the widely used ROOT project. His work spans end-to-end ML pipelines, from feature engineering with scikit-learn/Keras to GPU-accelerated components (CUDA) and production tooling like Docker, Kubernetes and cloud platforms. As a university tutor he translates complex physics and ML concepts for diverse audiences, while his INFN/CERN roles show an ability to operate in large, collaborative scientific software ecosystems. Less obvious is his habit of bridging research-grade code and production reliability, focusing on error handling and flexible execution flows in core analysis tools.
9 years of coding experience
Laurea Magistrale LM, Physics, 110/110 con Lode, Laurea Magistrale LM, Physics, 110/110 con Lode at Alma Mater Studiorum - Università di Bologna
Github Skills (8)
cer10
statistics10
c-language10
cprogramming-language10
r10
data-analysis10
parallel9
python8
Programming languages (5)
Github contributions (5)
root-project/root
Sep 2016 - Sep 2016
The official repository for ROOT: analyzing, storing and visualizing big data, scientifically
Role in this project:
Back-end Developer
Back-end DeveloperContributions:22 commits, 2 PRs, 1 comment in 17 days
Contributions summary:Luca primarily contributed to the `TSimpleAnalysis` class, which appears to be central to the ROOT project's data analysis capabilities. They made several modifications to this class, including changes to the `Run` and `Configure` functions, indicating involvement in the core logic and execution flow. Their work included handling tree names, managing input files, and ensuring the correct execution of analysis tasks, suggesting a focus on the backend aspects of the data analysis process. These changes focused on error handling and improving the flexibility of how the class is used.
pythonroot-cernmathematicsc-plus-plusscientific-visualization
infn-datacloud/orchestrator
Nov 2023 - Mar 2025
The INDIGO PaaS Orchestrator
Contributions:4 releases, 3 reviews, 13 PRs in 1 year 4 months
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