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Gian Michele Innocenti

PROFILE

Gian Michele Innocenti

Developed and maintained the MITHIGAnalysis2024 repository, delivering a robust suite of high energy physics analysis tools and workflows. Over seven months, built end-to-end data pipelines for jet, muon, and D0 meson studies, integrating C++ and Python with the ROOT framework for efficient data processing, simulation, and machine learning optimization. Enhanced reproducibility and maintainability through rigorous documentation, code refactoring, and standardized code review processes. Introduced modular analysis frameworks, dynamic environment setup, and debugging utilities to streamline onboarding and collaboration. The work enabled scalable, reproducible physics analyses across real and simulated datasets, supporting advanced studies in particle and nuclear physics.

Overall Statistics

Feature vs Bugs

96%Features

Repository Contributions

47Total
Bugs
1
Commits
47
Features
22
Lines of code
10,114
Activity Months7

Work History

November 2025

5 Commits • 3 Features

Nov 1, 2025

Month 2025-11 performance summary for ginnocen/MITHIGAnalysis2024 focused on delivering an end-to-end analysis framework, debugging and visualization utilities, and physics fidelity improvements to enable robust RAA studies across colliding systems. The work emphasizes business value through faster iteration, reproducible workflows, and higher quality physics outputs, demonstrating strong technical execution across C++/ROOT, Python, and data workflows.

June 2025

3 Commits • 3 Features

Jun 1, 2025

June 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).

May 2025

6 Commits • 3 Features

May 1, 2025

May 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, 2025

January 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.

December 2024

10 Commits • 7 Features

Dec 1, 2024

December 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, 2024

Month: 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.

October 2024

3 Commits • 1 Features

Oct 1, 2024

Month 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

Correctness86.4%
Maintainability85.0%
Architecture85.0%
Performance77.4%
AI Usage20.0%

Skills & Technologies

Programming Languages

BashC++INIMakefileMarkdownPythonShell

Technical Skills

Bash ScriptingBuild SystemsC++C++ DevelopmentC++ ProgrammingC++ ScriptingC++ programmingCMS SoftwareCode OrganizationCode RefactoringCode Review ProcessData AnalysisData Analysis ConfigurationData Analysis WorkflowData Processing

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

ginnocen/MITHIGAnalysis2024

Oct 2024 Nov 2025
7 Months active

Languages Used

MarkdownBashC++MakefilePythonShellINI

Technical Skills

DocumentationC++C++ DevelopmentC++ ProgrammingCMS SoftwareCode Organization