
Over five months, contributed to SBNSoftware repositories by enhancing trigger data processing, optimizing Monte Carlo workflows, and improving PMT decoder reliability. Focused on C++ and FCL, implemented end-to-end trigger emulation support, refined data structures, and streamlined configuration management to improve analysis fidelity and runtime performance. Addressed build system maintenance in sbndcode, clarified Monte Carlo configuration, and reduced onboarding time. Improved data quality by tuning MonThreshold parameters and optimizing the data processing pipeline, including the removal of unnecessary monitoring pulse data. Demonstrated strong debugging, error handling, and version control practices, resulting in more robust, maintainable, and efficient software systems.
January 2026 monthly summary for SBNSoftware/sbndcode. Delivered data processing pipeline optimization by removing monitoring pulse data from the reco1 configuration. This change reduces the data handling footprint at the earliest reconstruction stage, simplifying configuration and improving processing throughput. The work was implemented in a single, well-traced commit (bb7c35926d913499c751f4fc99da0bc0b84c41e4) that drops MonPulses and MonPulseSizes at the reco1 level. Impact: faster runs, lower maintenance burden, easier future configuration refinements. Skills demonstrated: configuration management, impact analysis, precise git-based change tracking, and collaboration within the SBND codebase.
January 2026 monthly summary for SBNSoftware/sbndcode. Delivered data processing pipeline optimization by removing monitoring pulse data from the reco1 configuration. This change reduces the data handling footprint at the earliest reconstruction stage, simplifying configuration and improving processing throughput. The work was implemented in a single, well-traced commit (bb7c35926d913499c751f4fc99da0bc0b84c41e4) that drops MonPulses and MonPulseSizes at the reco1 level. Impact: faster runs, lower maintenance burden, easier future configuration refinements. Skills demonstrated: configuration management, impact analysis, precise git-based change tracking, and collaboration within the SBND codebase.
December 2025 monthly summary for SBNSoftware/sbndcode: Focused on tuning Monte Carlo data processing parameters to improve accuracy and trigger response; performed targeted fixes to MonThreshold FCL parameters; improved MC-data alignment and trigger reliability; reinforced configuration management with traceable commits.
December 2025 monthly summary for SBNSoftware/sbndcode: Focused on tuning Monte Carlo data processing parameters to improve accuracy and trigger response; performed targeted fixes to MonThreshold FCL parameters; improved MC-data alignment and trigger reliability; reinforced configuration management with traceable commits.
November 2025: Focused work on PMT decoder reliability and analytics enhancements in SBNSoftware/sbndcode. Implemented critical fixes and analytics to improve data quality, channel handling, and cross-run baseline management, enabling more accurate physics analyses and robust data processing pipelines.
November 2025: Focused work on PMT decoder reliability and analytics enhancements in SBNSoftware/sbndcode. Implemented critical fixes and analytics to improve data quality, channel handling, and cross-run baseline management, enabling more accurate physics analyses and robust data processing pipelines.
October 2025 (SBNSoftware/sbndcode): Delivered configuration and build maintenance improvements focused on Monte Carlo workflow clarity and streamlined builds. The changes reduce maintenance overhead, improve reliability of Monte Carlo simulations, and clarify configuration for faster onboarding and consistent deployment.
October 2025 (SBNSoftware/sbndcode): Delivered configuration and build maintenance improvements focused on Monte Carlo workflow clarity and streamlined builds. The changes reduce maintenance overhead, improve reliability of Monte Carlo simulations, and clarify configuration for faster onboarding and consistent deployment.
September 2025 monthly summary: Focused on trigger data enhancements to improve analysis fidelity, runtime performance, and debugging visibility. Implemented end-to-end trigger emulation support across two repositories with data-structure refinements, new trigger fields, and production-time data filling, enabling more robust analysis pipelines and reproducibility.
September 2025 monthly summary: Focused on trigger data enhancements to improve analysis fidelity, runtime performance, and debugging visibility. Implemented end-to-end trigger emulation support across two repositories with data-structure refinements, new trigger fields, and production-time data filling, enabling more robust analysis pipelines and reproducibility.

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