EMPHATICSoft/emphaticsoft
Nov 2024 – Sep 2025
6 Months active
Languages Used
C++fclPythonTextFCLCMake
Technical Skills
C++C++ DevelopmentCode RefactoringData AcquisitionData StructuresEmbedded Systems
Manuel Dallolio
PROFILE
Manuel Dallolio
Manuel Del Tutto developed and integrated advanced ARICH detector simulation, reconstruction, and machine learning-based particle identification features within the EMPHATICSoft/emphaticsoft repository. He implemented end-to-end data flows for ARICH digitization, track association, and particle identification, leveraging C++ and CMake for robust code organization and maintainability. His work included integrating PyTorch-based neural networks for real-time inference, standardizing configuration management with FCL, and modernizing the codebase for consistency and future scalability. By refining data structures, improving channel mapping accuracy, and enforcing naming conventions, Manuel delivered deep, production-ready solutions that enhanced data quality, analysis readiness, and maintainability across the EMPHATICSoft platform.
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
10Total
Bugs
1
Commits
10
Features
7
Lines of code
17,358
Activity Months6
Your Network
15 peopleSame Organization
@emphaticgpvm02.fnal.gov1
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025Monthly performance summary for Sep 2025 focused on EMPHATICSoft/emphaticsoft with an emphasis on configuration quality, naming consistency, and maintainability.
1 Commits • 1 Features
Sep 1, 2025Monthly performance summary for Sep 2025 focused on EMPHATICSoft/emphaticsoft with an emphasis on configuration quality, naming consistency, and maintainability.
September 2025
August 2025
1 Commits • 1 Features
Aug 1, 2025Month: 2025-08 — Focus on ML-driven particle identification for ARICH; integrated PyTorch model with C++ runtime; added configuration for model path; groundwork for production-ready ML inference in the EMPHATICSoft pipeline.
August 2025
1 Commits • 1 Features
Aug 1, 2025Month: 2025-08 — Focus on ML-driven particle identification for ARICH; integrated PyTorch model with C++ runtime; added configuration for model path; groundwork for production-ready ML inference in the EMPHATICSoft pipeline.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025: Completed end-to-end ARICH reconstruction integration with tracks and PID for EMPHATICSoft/emphaticsoft. Implemented sequencing to call ARICH reconstruction after track generation, enabling the Track Filler to populate ARICH-associated objects and leverage track information for improved particle identification. Updated ARICH reconstruction modules to support the new workflow and aligned prod_reco sequencing for a streamlined ARICH/PID path. This work establishes a solid foundation for end-to-end ARICH-based analyses and enhances data quality.
1 Commits • 1 Features
May 1, 2025May 2025: Completed end-to-end ARICH reconstruction integration with tracks and PID for EMPHATICSoft/emphaticsoft. Implemented sequencing to call ARICH reconstruction after track generation, enabling the Track Filler to populate ARICH-associated objects and leverage track information for improved particle identification. Updated ARICH reconstruction modules to support the new workflow and aligned prod_reco sequencing for a streamlined ARICH/PID path. This work establishes a solid foundation for end-to-end ARICH-based analyses and enhances data quality.
May 2025
January 2025
3 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for EMPHATICSoft/emphaticsoft. Focused on data-quality improvements for ARICH/SSD classifications and foundational codebase modernization to improve reliability, developer velocity, and future readiness. Key business impacts include improved accuracy of channel mappings, reduced maintenance burden through standardized naming and API surfaces, and clearer change management.
January 2025
3 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for EMPHATICSoft/emphaticsoft. Focused on data-quality improvements for ARICH/SSD classifications and foundational codebase modernization to improve reliability, developer velocity, and future readiness. Key business impacts include improved accuracy of channel mappings, reduced maintenance burden through standardized naming and API surfaces, and clearer change management.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024: EMPHATICSoft/emphaticsoft – Delivered ARICH detector simulation and reconstruction feature, enhancing particle identification modeling within the EMPHATIC framework. Established detector parameterization, aerogel properties, and Cherenkov radiation core logic; expanded the repository with essential utility classes and data files to enable end-to-end ARICH simulation and reconstruction. No major defects fixed this month; the focus was on feature development and infrastructure for future bug fixes and improvements.
1 Commits • 1 Features
Dec 1, 2024December 2024: EMPHATICSoft/emphaticsoft – Delivered ARICH detector simulation and reconstruction feature, enhancing particle identification modeling within the EMPHATIC framework. Established detector parameterization, aerogel properties, and Cherenkov radiation core logic; expanded the repository with essential utility classes and data files to enable end-to-end ARICH simulation and reconstruction. No major defects fixed this month; the focus was on feature development and infrastructure for future bug fixes and improvements.
December 2024
November 2024
3 Commits • 2 Features
Nov 1, 2024November 2024: Delivered substantial enhancements to ARICH digitization and detector data modeling in EMPHATICSoft/emphaticsoft, enabling more accurate data association and streamlined downstream analysis. Implemented data-handling enhancements and standard records to support PID and ArichID integration, improving data traceability and analysis readiness.
November 2024
3 Commits • 2 Features
Nov 1, 2024November 2024: Delivered substantial enhancements to ARICH digitization and detector data modeling in EMPHATICSoft/emphaticsoft, enabling more accurate data association and streamlined downstream analysis. Implemented data-handling enhancements and standard records to support PID and ArichID integration, improving data traceability and analysis readiness.
Activity
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Quality Metrics
Correctness84.0%
Maintainability86.0%
Architecture82.0%
Performance72.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++CMakeFCLPythonTextfcl
Technical Skills
Build SystemsC++C++ DevelopmentCMakeCherenkov RadiationCode OrganizationCode RefactoringConfiguration ManagementData AcquisitionData AnalysisData ConfigurationData ReconstructionData StructuresDeep LearningDetector Simulation
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