
Over 14 months, contributed to SBNSoftware/sbndcode and related repositories by developing and refining data acquisition, simulation, and trigger systems for particle physics experiments. Focused on C++ and CMake, the work included implementing configurable noise filtering, enhancing timing synchronization, and integrating software triggers to improve data quality and analysis reliability. Leveraged configuration management and data processing skills to centralize and standardize settings, reduce misconfiguration risk, and streamline detector simulation workflows. Addressed bugs in data integrity and simulation accuracy, while introducing new features for metric analysis and event reconstruction. The engineering approach emphasized maintainability, traceability, and alignment with evolving DAQ requirements.
December 2025 SBND codebase: No new features delivered this month. Focused on correctness, configuration clarity, and maintainability in the detector simulation path. Implemented two core bug fixes and completed code cleanup to reduce maintenance overhead and improve reliability.
December 2025 SBND codebase: No new features delivered this month. Focused on correctness, configuration clarity, and maintainability in the detector simulation path. Implemented two core bug fixes and completed code cleanup to reduce maintenance overhead and improve reliability.
Month 2025-11: Delivered end-to-end software trigger capabilities and data-tracking enhancements across SBNSoftware repos, with a strong focus on business value, maintainability, and DAQ alignment. Implemented cross-repo trigger support, improved event accounting, and cleaned up build/configuration for easier maintenance and deployment. The work enhances trigger-driven analyses, optimizes data processing flows, and reduces operational risk through clearer naming and documentation.
Month 2025-11: Delivered end-to-end software trigger capabilities and data-tracking enhancements across SBNSoftware repos, with a strong focus on business value, maintainability, and DAQ alignment. Implemented cross-repo trigger support, improved event accounting, and cleaned up build/configuration for easier maintenance and deployment. The work enhances trigger-driven analyses, optimizes data processing flows, and reduces operational risk through clearer naming and documentation.
Worked on 2 features and fixed 0 bugs across 1 repositories.
Worked on 2 features and fixed 0 bugs across 1 repositories.
Month: 2025-09. Focused on data integrity in SBNSoftware/sbndaq-artdaq by implementing input validation in the data processing pipeline. Delivered a container-length check to prevent processing of empty or malformed data, reducing errors and improving reliability. Commit 082e8c2a20cc14b2eb5e28eee521238cb72339b1 ('add check for container length'). Impact: higher data quality, fewer pipeline failures, and smoother downstream analytics. Technologies/skills demonstrated include defensive programming, Git-based change management, and data validation patterns.
Month: 2025-09. Focused on data integrity in SBNSoftware/sbndaq-artdaq by implementing input validation in the data processing pipeline. Delivered a container-length check to prevent processing of empty or malformed data, reducing errors and improving reliability. Commit 082e8c2a20cc14b2eb5e28eee521238cb72339b1 ('add check for container length'). Impact: higher data quality, fewer pipeline failures, and smoother downstream analytics. Technologies/skills demonstrated include defensive programming, Git-based change management, and data validation patterns.
In August 2025, delivered a targeted data quality improvement for the SBND codebase (SBNSoftware/sbndcode) by tightening the deconvolution threshold to reduce signal contamination. The change enhances data processing accuracy and reliability by refining the deconvolution step, implemented via a JSONNET configuration update in chndb-base.jsonnet.
In August 2025, delivered a targeted data quality improvement for the SBND codebase (SBNSoftware/sbndcode) by tightening the deconvolution threshold to reduce signal contamination. The change enhances data processing accuracy and reliability by refining the deconvolution step, implemented via a JSONNET configuration update in chndb-base.jsonnet.
July 2025 focused on delivering feature work, stabilizing configurations, and improving simulation fidelity in SBND. Key outcomes include configuration standardization for maintainability, integration and tuning of ccnuefilter in SBND pipelines, careful management of DNN ROI changes with rollback for stability, and targeted signal processing tuning in WireCell to improve robustness. These efforts reduce false positives, improve readability, and accelerate reliable physics analyses, enabling more efficient downstream experiments and decision-making.
July 2025 focused on delivering feature work, stabilizing configurations, and improving simulation fidelity in SBND. Key outcomes include configuration standardization for maintainability, integration and tuning of ccnuefilter in SBND pipelines, careful management of DNN ROI changes with rollback for stability, and targeted signal processing tuning in WireCell to improve robustness. These efforts reduce false positives, improve readability, and accelerate reliable physics analyses, enabling more efficient downstream experiments and decision-making.
May 2025 performance summary for SBNSoftware/sbndcode: delivered configurable coherent noise filtering and robust bug fixes that improve data quality and processing efficiency. Implemented new configuration parameters 'correlation_threshold' and 'default_scaling' to finer-tune coherent noise removal, and fixed channel grouping and dead-channel handling by reducing group size from 128 to 64 and introducing special grouping to accommodate up to 32 dead channels on the collection plane.
May 2025 performance summary for SBNSoftware/sbndcode: delivered configurable coherent noise filtering and robust bug fixes that improve data quality and processing efficiency. Implemented new configuration parameters 'correlation_threshold' and 'default_scaling' to finer-tune coherent noise removal, and fixed channel grouping and dead-channel handling by reducing group size from 128 to 64 and introducing special grouping to accommodate up to 32 dead channels on the collection plane.
April 2025 monthly summary for SBNSoftware/sbndcode. Focused on configuration governance to improve reliability and consistency of optical channel masking across operational modes. Implemented centralized masking configuration by moving from a data-specific configuration file (FCL) to the main option/configuration file. Updated the main configuration to reflect the specific masked channels, enabling consistent deployments and easier maintenance.
April 2025 monthly summary for SBNSoftware/sbndcode. Focused on configuration governance to improve reliability and consistency of optical channel masking across operational modes. Implemented centralized masking configuration by moving from a data-specific configuration file (FCL) to the main option/configuration file. Updated the main configuration to reflect the specific masked channels, enabling consistent deployments and easier maintenance.
March 2025 performance summary for SBNSoftware/sbndcode: Delivered targeted configuration changes to improve data quality, reproducibility, and processing efficiency. Key deliverables include adding a dataTier parameter to metric filter output, aligning simulation vs reconstruction timing via ctoffset adjustment, and updating PMT efficiencies in OpT0Finder configurations for both job and data configurations. These changes enhance data processing accuracy and detector-response fidelity with clear commit-level traceability. Skills demonstrated include FCL/JSONNET configuration management, version-controlled parameter tuning, and end-to-end data workflow optimization.
March 2025 performance summary for SBNSoftware/sbndcode: Delivered targeted configuration changes to improve data quality, reproducibility, and processing efficiency. Key deliverables include adding a dataTier parameter to metric filter output, aligning simulation vs reconstruction timing via ctoffset adjustment, and updating PMT efficiencies in OpT0Finder configurations for both job and data configurations. These changes enhance data processing accuracy and detector-response fidelity with clear commit-level traceability. Skills demonstrated include FCL/JSONNET configuration management, version-controlled parameter tuning, and end-to-end data workflow optimization.
February 2025 focused on delivering flexible data processing capabilities, improving timing synchronization, and strengthening the reliability of the SBND data reconstruction chain. Work concentrated on SBNSoftware/sbndcode with multiple feature enhancements and targeted bug fixes that enable more accurate physics analysis and streamlined configuration management across the pipeline.
February 2025 focused on delivering flexible data processing capabilities, improving timing synchronization, and strengthening the reliability of the SBND data reconstruction chain. Work concentrated on SBNSoftware/sbndcode with multiple feature enhancements and targeted bug fixes that enable more accurate physics analysis and streamlined configuration management across the pipeline.
During January 2025, SBNSoftware/sbndcode delivered a set of enhancements focused on offline processing, data quality improvements, and flexible configuration for DAQ-driven workflows. The work emphasizes reliability, reproducibility, and better alignment with physical hardware, enabling more robust offline analytics and accurate event-time associations.
During January 2025, SBNSoftware/sbndcode delivered a set of enhancements focused on offline processing, data quality improvements, and flexible configuration for DAQ-driven workflows. The work emphasizes reliability, reproducibility, and better alignment with physical hardware, enabling more robust offline analytics and accurate event-time associations.
December 2024: Delivered substantial timing infrastructure enhancements, a new PMT metric filtering pipeline, and robustness improvements in metric analysis within SBNSoftware/sbndcode. Changes emphasize data quality, configurability, and cross-subsystem accessibility, translating to reliable live data processing, easier maintenance, and clearer configuration paths across subsystems.
December 2024: Delivered substantial timing infrastructure enhancements, a new PMT metric filtering pipeline, and robustness improvements in metric analysis within SBNSoftware/sbndcode. Changes emphasize data quality, configurability, and cross-subsystem accessibility, translating to reliable live data processing, easier maintenance, and clearer configuration paths across subsystems.
Summary for 2024-11 (SBNSoftware/sbndcode): This period focused on boosting simulation timing fidelity and expanding PMT timing data products and analytics. Key features delivered include: (1) RC timing parameter tuning to improve simulation accuracy (update nticks, RC width, and related filter time constants); committed as 26d0da710315ea48c8602f09b10d1814059548a0, with follow-ups f6d2f36f0ee8bdfac274ac8ab92fa8e8be4a09f6 and 8642baf3f777569205442ebaf4ac5b320f2e5e93 to update RC response values. (2) PMT timing data products and analytics: new timing data structures, timing extraction improvements, PTB timing reference, rollover handling for triggers, and a new MetricAnalyzer for PMT metrics; commits include 9da858ec3711d4052eed78c7951681e4e8756132, f78ec73fa9284beacd96d6389b69ca0b28073d56, 89a589c98aa5188feb67cea2db7004972128a17d, 603513a37a0c4b39ce72d3b526168fc1a31a6e7c, 97541144569ac6850bdc1ab8350f5e8d6c9b7401, ee790095989ef8d8c59ee9331c798e1790f78d26. (3) Robustness improvements for rollover handling and extended waveforms, including support for multiple triggerTimeTag and rollover checks; commits 89a589c98..., 603513a37..., 97541144.... (4) Bug fixes for timing calculations, including correcting tdc calculation and RC timing alignment; visible in commits 89a589c98aa5188feb67cea2db7004972128a17d and earlier RC updates.
Summary for 2024-11 (SBNSoftware/sbndcode): This period focused on boosting simulation timing fidelity and expanding PMT timing data products and analytics. Key features delivered include: (1) RC timing parameter tuning to improve simulation accuracy (update nticks, RC width, and related filter time constants); committed as 26d0da710315ea48c8602f09b10d1814059548a0, with follow-ups f6d2f36f0ee8bdfac274ac8ab92fa8e8be4a09f6 and 8642baf3f777569205442ebaf4ac5b320f2e5e93 to update RC response values. (2) PMT timing data products and analytics: new timing data structures, timing extraction improvements, PTB timing reference, rollover handling for triggers, and a new MetricAnalyzer for PMT metrics; commits include 9da858ec3711d4052eed78c7951681e4e8756132, f78ec73fa9284beacd96d6389b69ca0b28073d56, 89a589c98aa5188feb67cea2db7004972128a17d, 603513a37a0c4b39ce72d3b526168fc1a31a6e7c, 97541144569ac6850bdc1ab8350f5e8d6c9b7401, ee790095989ef8d8c59ee9331c798e1790f78d26. (3) Robustness improvements for rollover handling and extended waveforms, including support for multiple triggerTimeTag and rollover checks; commits 89a589c98..., 603513a37..., 97541144.... (4) Bug fixes for timing calculations, including correcting tdc calculation and RC timing alignment; visible in commits 89a589c98aa5188feb67cea2db7004972128a17d and earlier RC updates.
2024-10 monthly summary for SBNSoftware/sbndcode: Delivered stabilization improvements to noise filtering, including standardized tick inheritance and complete channel-group coverage, leading to more consistent data processing. Reverted recent coherent noise filter tuning and disabled grouped noise filtering in simulations to restore prior behavior and reduce simulation discrepancies. Overall, these changes improve data quality, reliability of simulations, and downstream analytics, with clear business value in more predictable results and reduced debugging time.
2024-10 monthly summary for SBNSoftware/sbndcode: Delivered stabilization improvements to noise filtering, including standardized tick inheritance and complete channel-group coverage, leading to more consistent data processing. Reverted recent coherent noise filter tuning and disabled grouped noise filtering in simulations to restore prior behavior and reduce simulation discrepancies. Overall, these changes improve data quality, reliability of simulations, and downstream analytics, with clear business value in more predictable results and reduced debugging time.

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