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AndyChappell

PROFILE

Andychappell

Andrew Chappell developed advanced particle reconstruction features for the DUNE/dunereco and SBNSoftware/sbndcode repositories, focusing on low-energy neutrino event processing and particle flow analysis. He enhanced Pandora XML configurations and designed algorithms in C++ and Python to improve clustering, vertexing, and particle recovery, introducing dedicated workflows for high-density datasets. In SBNSoftware/sbndcode, Andrew implemented a merging algorithm for MIP-like stubs and shower cascades, recalibrating PFO scores to refine track and shower discrimination. His work integrated machine learning techniques, such as Boosted Decision Trees, and demonstrated strong workflow management, resulting in deeper analysis capabilities and more robust physics event reconstruction pipelines.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

5Total
Bugs
0
Commits
5
Features
3
Lines of code
1,825
Activity Months3

Work History

January 2026

2 Commits • 1 Features

Jan 1, 2026

January 2026 (SBNSoftware/sbndcode): Focused on advancing particle flow reconstruction. Key feature delivered: a merging algorithm to combine MIP-like stubs with shower cascades from split primary electrons, and recalibration of PFO scores after potential electron merges to improve track/shower analysis. This work enhances reconstruction accuracy for electron-rich events and reduces misidentification between tracks and showers. The changes are implemented in SBNSoftware/sbndcode with commits 61db99a83b479d57faa6c3c059e50c2a03913a8c and 8a6de3ffb518311cad9c5d5c20ac1642fc9acae8. Major bugs fixed: none reported in this scope; focus has been on feature development and integration. Overall impact: improved particle flow reconstruction, better track/shower discrimination, and a foundation for more robust physics analyses. Technologies/skills demonstrated: algorithm design for particle flow, MIP-like stub/shower merging, PFO score recalibration, code integration into a large software repository, and version control discipline.

December 2024

1 Commits • 1 Features

Dec 1, 2024

December 2024: Delivered production-network aware LowE workflow enhancements with Boosted Decision Trees (BDTs) integration for DUNE/dunereco. This update aligns the workflow with production environments and enhances analytical capabilities by integrating BDT-driven data processing steps and models.

October 2024

2 Commits • 1 Features

Oct 1, 2024

October 2024: DUNE/dunereco contributed enhancements to the Pandora XML configuration for low-energy neutrino detection and event reconstruction. This included new XML configurations and workflow tuning for low-energy processing, improving clustering, vertexing, and particle recovery accuracy. Added a dedicated Pandora low-energy workflow for HD datasets to support higher-density event reconstruction. Overall, feature-focused month with no critical bugs reported and strong alignment to business goals of improved sensitivity and data quality.

Activity

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Quality Metrics

Correctness88.0%
Maintainability80.0%
Architecture88.0%
Performance80.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

C++PythonXML

Technical Skills

C++ DevelopmentData AnalysisMachine LearningPython DevelopmentWorkflow ManagementXML configurationalgorithm designalgorithm developmentdata analysisdata processingneutrino physicsparticle physics

Repositories Contributed To

2 repos

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

DUNE/dunereco

Oct 2024 Dec 2024
2 Months active

Languages Used

XMLC++Python

Technical Skills

XML configurationalgorithm designalgorithm developmentdata processingneutrino physicsC++ Development

SBNSoftware/sbndcode

Jan 2026 Jan 2026
1 Month active

Languages Used

XML

Technical Skills

XML configurationalgorithm developmentdata analysisdata processingparticle physics