ginnocen/MITHIGAnalysis2024
Oct 2024 – Jun 2025
6 Months active
Languages Used
MarkdownBashC++MakefilePythonShellINI
Technical Skills
DocumentationC++C++ DevelopmentC++ ProgrammingCMS SoftwareCode Organization
Gian Michele Innocenti
PROFILE
Gian Michele Innocenti
Giovanni Minnicelli developed and maintained the MITHIGAnalysis2024 repository, delivering a robust suite of high energy physics analysis tools for jet, muon, and meson studies. He architected modular C++ and Python workflows for data processing, event selection, and machine learning-based signal optimization, integrating technologies such as ROOT, XGBoost, and Bash scripting. His work included building scalable analysis frameworks for Oxygen-Oxygen collisions, implementing track-by-track corrections, and automating environment setup. Giovanni emphasized code organization, reproducibility, and maintainability, introducing standardized code review processes and detailed documentation. The resulting platform enabled reliable, extensible physics analyses and streamlined collaboration across data and Monte Carlo samples.
Overall Statistics
Feature vs Bugs
95%Features
Repository Contributions
42Total
Bugs
1
Commits
42
Features
19
Lines of code
8,840
Activity Months6
Your Network
5 people
Work History
June 2025
3 Commits • 3 Features
Jun 1, 2025June 2025 focused on delivering core physics analytics capabilities for OO collisions, enabling more reliable data processing and faster physics insights, along with improvements to data-quality corrections and development workflow. Key outcomes include the introduction of two new analysis frameworks and a standardized code-review process that supports repeatable, reviewable changes across the repository. Key achievements: - OO Collision Main Analysis Framework delivered: new executable, scripts, and parameter/utility headers; refined data processing for OO and PP (commit a2b861d124cf257638d91dd262463772ee782746). - Charged Hadron Analysis Framework with track-by-track corrections; updated Messenger with track properties; new executable and supporting scripts; added standard cuts filter (commit 9280c69ff5d742fe37fd13bd248fd8d3ea366494). - Code-Review Workflow Documentation updated in README to standardize PR handling and review requests (commit 646e74ee6e4d4518beb5ccc155ab7edf1cf6f529).
3 Commits • 3 Features
Jun 1, 2025June 2025 focused on delivering core physics analytics capabilities for OO collisions, enabling more reliable data processing and faster physics insights, along with improvements to data-quality corrections and development workflow. Key outcomes include the introduction of two new analysis frameworks and a standardized code-review process that supports repeatable, reviewable changes across the repository. Key achievements: - OO Collision Main Analysis Framework delivered: new executable, scripts, and parameter/utility headers; refined data processing for OO and PP (commit a2b861d124cf257638d91dd262463772ee782746). - Charged Hadron Analysis Framework with track-by-track corrections; updated Messenger with track properties; new executable and supporting scripts; added standard cuts filter (commit 9280c69ff5d742fe37fd13bd248fd8d3ea366494). - Code-Review Workflow Documentation updated in README to standardize PR handling and review requests (commit 646e74ee6e4d4518beb5ccc155ab7edf1cf6f529).
June 2025
May 2025
6 Commits • 3 Features
May 1, 2025May 2025 monthly summary for ginnocen/MITHIGAnalysis2024. The month focused on establishing OO RAA analysis foundations and expanding data analysis capabilities, delivering foundational scaffolding, an OO RAA data analysis toolkit, skim/data structure enhancements, and sample configuration updates with debug support. These efforts lay the groundwork for scalable OO RAA analyses, improve data processing workflows, and enable broader MC studies while reducing debugging friction.
May 2025
6 Commits • 3 Features
May 1, 2025May 2025 monthly summary for ginnocen/MITHIGAnalysis2024. The month focused on establishing OO RAA analysis foundations and expanding data analysis capabilities, delivering foundational scaffolding, an OO RAA data analysis toolkit, skim/data structure enhancements, and sample configuration updates with debug support. These efforts lay the groundwork for scalable OO RAA analyses, improve data processing workflows, and enable broader MC studies while reducing debugging friction.
January 2025
4 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for ginnocen/MITHIGAnalysis2024 focused on delivering a robust machine learning pipeline to optimize D0 meson signal using XGBoost. The work spans data ingestion from ROOT files, feature engineering, model training and evaluation, and setup for maintainability and code quality. Key data path adjustments for Monte Carlo inputs were completed to ensure reproducible experiments, alongside validation and visualization components (feature importance, ROC curves) to enable transparent model assessment. A refactor of the ML optimization workflow and formatting improvements were implemented to improve readability, maintainability, and deployment readiness. The assets laid groundwork for more accurate signal extraction and smoother collaboration across the team.
4 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for ginnocen/MITHIGAnalysis2024 focused on delivering a robust machine learning pipeline to optimize D0 meson signal using XGBoost. The work spans data ingestion from ROOT files, feature engineering, model training and evaluation, and setup for maintainability and code quality. Key data path adjustments for Monte Carlo inputs were completed to ensure reproducible experiments, alongside validation and visualization components (feature importance, ROC curves) to enable transparent model assessment. A refactor of the ML optimization workflow and formatting improvements were implemented to improve readability, maintainability, and deployment readiness. The assets laid groundwork for more accurate signal extraction and smoother collaboration across the team.
January 2025
December 2024
10 Commits • 7 Features
Dec 1, 2024December 2024 (Month: 2024-12) performance summary for ginnocen/MITHIGAnalysis2024. Delivered a cohesive set of features and reliability improvements enabling detailed jet and muon analysis, streamlined environment setup, and robust data/MC workflows. The work focused on expanding physics capabilities, improving data quality, and enhancing reproducibility across datasets and MC samples.
December 2024
10 Commits • 7 Features
Dec 1, 2024December 2024 (Month: 2024-12) performance summary for ginnocen/MITHIGAnalysis2024. Delivered a cohesive set of features and reliability improvements enabling detailed jet and muon analysis, streamlined environment setup, and robust data/MC workflows. The work focused on expanding physics capabilities, improving data quality, and enhancing reproducibility across datasets and MC samples.
November 2024
16 Commits • 4 Features
Nov 1, 2024Month: 2024-11. This period delivered a cohesive set of enhancements to the MITHIGAnalysis2024 project across generator-level data enrichment, dimuon-jet studies, and processing workflow improvements. The work improved analysis fidelity, expanded study capabilities for real data and MC, and strengthened maintainability of the production pipeline.
16 Commits • 4 Features
Nov 1, 2024Month: 2024-11. This period delivered a cohesive set of enhancements to the MITHIGAnalysis2024 project across generator-level data enrichment, dimuon-jet studies, and processing workflow improvements. The work improved analysis fidelity, expanded study capabilities for real data and MC, and strengthened maintainability of the production pipeline.
November 2024
October 2024
3 Commits • 1 Features
Oct 1, 2024Month 2024-10: Established the foundational setup for the MITHIGAnalysis2024 project with a strong emphasis on repository hygiene and documentation readiness. The work focused on creating a clear onboarding baseline and aligning the project with its intended framework, enabling faster contribution and future feature development.
October 2024
3 Commits • 1 Features
Oct 1, 2024Month 2024-10: Established the foundational setup for the MITHIGAnalysis2024 project with a strong emphasis on repository hygiene and documentation readiness. The work focused on creating a clear onboarding baseline and aligning the project with its intended framework, enabling faster contribution and future feature development.
Activity
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Quality Metrics
Correctness87.2%
Maintainability85.6%
Architecture85.8%
Performance77.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
BashC++INIMakefileMarkdownPythonShell
Technical Skills
Bash ScriptingBuild SystemsC++C++ DevelopmentC++ ProgrammingC++ ScriptingCMS SoftwareCode OrganizationCode RefactoringCode Review ProcessData AnalysisData Analysis ConfigurationData Analysis WorkflowData ProcessingData Reduction
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