DUNE/ndlar_flow
Apr 2025 – Jan 2026
7 Months active
Languages Used
PythonYAMLyamlC++
Technical Skills
Code FormattingConfiguration ManagementData AnalysisData ConfigurationData ProcessingDetector Simulation
James Vincent Mead
PROFILE
James Vincent Mead
James Mead developed advanced waveform processing and hit-finding capabilities for the DUNE/ndlar_flow repository, focusing on robust data quality and configurable analysis pipelines. Over seven months, he engineered features such as dynamic baselining, RMS-based noise thresholding, and configurable time-over-threshold detection, using Python and YAML-driven configuration. His work included refactoring algorithms for reliability, integrating CI/CD workflows with GitHub Actions, and improving maintainability through code cleanup and explicit configuration management. By addressing edge cases, optimizing numerical methods, and enhancing signal processing, James enabled more accurate hit detection and streamlined downstream analytics, demonstrating depth in scientific computing and software engineering practices.
Overall Statistics
Feature vs Bugs
81%Features
Repository Contributions
62Total
Bugs
4
Commits
62
Features
17
Lines of code
1,028,226
Activity Months7
Your Network
29 people
Work History
January 2026
2 Commits • 1 Features
Jan 1, 2026January 2026: DUNE/ndlar_flow delivered waveform processing enhancements to improve data quality and hit-detection accuracy. Implemented dynamic baselining in WaveformNoiseFilter and adjusted thresholds in WaveformHitFinder. Removed hard-coded default baselining parameter to enable flexible configuration and fixed TOT calculation thresholds to improve accuracy. These changes reduce false positives and simplify future tuning, demonstrating strong algorithmic work and maintainable code changes.
2 Commits • 1 Features
Jan 1, 2026January 2026: DUNE/ndlar_flow delivered waveform processing enhancements to improve data quality and hit-detection accuracy. Implemented dynamic baselining in WaveformNoiseFilter and adjusted thresholds in WaveformHitFinder. Removed hard-coded default baselining parameter to enable flexible configuration and fixed TOT calculation thresholds to improve accuracy. These changes reduce false positives and simplify future tuning, demonstrating strong algorithmic work and maintainable code changes.
January 2026
December 2025
6 Commits • 3 Features
Dec 1, 20252025-12 monthly summary for DUNE/ndlar_flow. Delivered key waveform-analysis capabilities with robust data handling and configurable detection parameters to improve data quality and reliability. Highlights include peak detection and light-fraction enhancements with a refactor of fprompt and pulse-shape extraction for reliability; NaN-safe RMS handling to suppress warnings; configurable time-over-threshold thresholds for hit finding; and dynamic baseline segmentation to improve noise filtering based on waveform length. Focused on reducing duplicates, memory issues, and improving test readiness while delivering measurable business value in data quality and detector signal processing.
December 2025
6 Commits • 3 Features
Dec 1, 20252025-12 monthly summary for DUNE/ndlar_flow. Delivered key waveform-analysis capabilities with robust data handling and configurable detection parameters to improve data quality and reliability. Highlights include peak detection and light-fraction enhancements with a refactor of fprompt and pulse-shape extraction for reliability; NaN-safe RMS handling to suppress warnings; configurable time-over-threshold thresholds for hit finding; and dynamic baseline segmentation to improve noise filtering based on waveform length. Focused on reducing duplicates, memory issues, and improving test readiness while delivering measurable business value in data quality and detector signal processing.
November 2025
16 Commits • 5 Features
Nov 1, 2025November 2025 monthly summary for DUNE/ndlar_flow. Focused on delivering robust hit finding, data quality improvements, and Run2 readiness to increase downstream analytics reliability and overall detector performance. Business value centers on higher hit-detection accuracy, reduced data quality issues, and stable processing for Run2 data.
16 Commits • 5 Features
Nov 1, 2025November 2025 monthly summary for DUNE/ndlar_flow. Focused on delivering robust hit finding, data quality improvements, and Run2 readiness to increase downstream analytics reliability and overall detector performance. Business value centers on higher hit-detection accuracy, reduced data quality issues, and stable processing for Run2 data.
November 2025
October 2025
8 Commits • 3 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on DUNE/ndlar_flow. This period delivered key features that improve waveform analysis reliability, enhanced configuration clarity, and strengthened testing, while fixing critical issues that impact measurement accuracy and data quality. The work emphasizes business value through more robust data processing, easier configuration, and improved QA/documentation.
October 2025
8 Commits • 3 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on DUNE/ndlar_flow. This period delivered key features that improve waveform analysis reliability, enhanced configuration clarity, and strengthened testing, while fixing critical issues that impact measurement accuracy and data quality. The work emphasizes business value through more robust data processing, easier configuration, and improved QA/documentation.
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for DUNE/ndlar_flow focusing on waveform processing robustness and pipeline reliability.
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for DUNE/ndlar_flow focusing on waveform processing robustness and pipeline reliability.
September 2025
May 2025
10 Commits • 2 Features
May 1, 2025May 2025: Delivered major reliability and data-quality improvements for DUNE/ndlar_flow. Key outcomes include groundwork toward vectorized fprompt calculations with improved noise thresholding and precise prompt window definitions, streamlined SumTPCHitFinder configuration, and stabilized geometry handling. These changes increase hit-detection reliability, reduce downstream analysis time, and improve maintainability by cleaning up configuration and runtime artifacts.
May 2025
10 Commits • 2 Features
May 1, 2025May 2025: Delivered major reliability and data-quality improvements for DUNE/ndlar_flow. Key outcomes include groundwork toward vectorized fprompt calculations with improved noise thresholding and precise prompt window definitions, streamlined SumTPCHitFinder configuration, and stabilized geometry handling. These changes increase hit-detection reliability, reduce downstream analysis time, and improve maintainability by cleaning up configuration and runtime artifacts.
April 2025
18 Commits • 2 Features
Apr 1, 2025April 2025: DUNE/ndlar_flow delivered configurable waveform processing enhancements, improved output standardization, and stability improvements to enable faster, reproducible analysis. Key features: (1) Waveform Sum Improvements and Output Naming — split tpc-summed waveforms by trap type, added dataset naming/config for stpc and light/stpc waveforms, and standardized output dataset names in WaveformSum.yaml (representative commits include 85a96d4 and c8f458d). (2) Hit Finder Enhancements: Multi-Mode Processing and SumTPC Integration — added multi-mode waveform processing (sum_tpc, sum, sipm), implemented SumTPC hit finder, and propagated config-driven parameters via YAML; workflow updates reflect config changes. (3) Stability and Quality — refactoring to fix arg handling, indentation, and merge hygiene, including changes from feature/mr6.4 and alignment with develop. (4) Business Impact and Tech Skills — improved configurability, reproducibility, and deployment readiness; standardized outputs accelerate experimentation and enable production workflows; demonstrated Python-based processing, YAML-config driven workflows, and Git-based version control.
18 Commits • 2 Features
Apr 1, 2025April 2025: DUNE/ndlar_flow delivered configurable waveform processing enhancements, improved output standardization, and stability improvements to enable faster, reproducible analysis. Key features: (1) Waveform Sum Improvements and Output Naming — split tpc-summed waveforms by trap type, added dataset naming/config for stpc and light/stpc waveforms, and standardized output dataset names in WaveformSum.yaml (representative commits include 85a96d4 and c8f458d). (2) Hit Finder Enhancements: Multi-Mode Processing and SumTPC Integration — added multi-mode waveform processing (sum_tpc, sum, sipm), implemented SumTPC hit finder, and propagated config-driven parameters via YAML; workflow updates reflect config changes. (3) Stability and Quality — refactoring to fix arg handling, indentation, and merge hygiene, including changes from feature/mr6.4 and alignment with develop. (4) Business Impact and Tech Skills — improved configurability, reproducibility, and deployment readiness; standardized outputs accelerate experimentation and enable production workflows; demonstrated Python-based processing, YAML-config driven workflows, and Git-based version control.
April 2025
Activity
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Quality Metrics
Correctness85.4%
Maintainability83.6%
Architecture82.2%
Performance78.2%
AI Usage21.2%
Skills & Technologies
Programming Languages
C++PythonYAMLyaml
Technical Skills
CI/CDCode CleanupCode FormattingConfiguration ManagementContinuous IntegrationData AnalysisData ConfigurationData ProcessingDebuggingDetector SimulationDevOpsGitHub ActionsNumerical ComputationPhysics SimulationPython
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