AllenNeuralDynamics/dynamic-foraging-task
Nov 2024 – Dec 2025
8 Months active
Languages Used
XMLBonsaiCSVPythonC#
Technical Skills
Data AcquisitionSystem IntegrationWorkflow DevelopmentBack-end DevelopmentBackend DevelopmentBehavioral Programming
Xinxin Yin
PROFILE
Xinxin Yin
Worked on the AllenNeuralDynamics/dynamic-foraging-task repository, delivering features and fixes that improved experimental workflow reliability, data integrity, and user control. Developed and refined Bonsai-based workflows for behavioral experiments, integrating camera and hardware controls, synchronizing data acquisition, and standardizing configuration management. Used Python, XML, and PyQt to enhance GUI layouts, automate metadata handling, and implement robust error handling and logging. Refactored code for maintainability, optimized workflow timing, and extended video data validation to support complex directory structures. The work emphasized reproducibility, streamlined experiment setup, and reduced operational risk, demonstrating depth in backend development, workflow optimization, and embedded systems integration.
Overall Statistics
Feature vs Bugs
56%Features
Repository Contributions
34Total
Bugs
8
Commits
34
Features
10
Lines of code
20,117
Activity Months8
Your Network
17 peopleSame Organization
@tsinghua.org.cn4
Work History
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025: Delivered a robust enhancement to the dynamic-foraging-task data pipeline by extending video frame integrity checks to support both flat and nested folder structures, bolstering data quality and traceability. Implemented improved error handling and logging for frame count discrepancies, enabling reliable monitoring of video data integrity across complex directory layouts. This work reduces manual data curation, improves reproducibility for downstream analyses, and reinforces the project’s data integrity standards. Demonstrated strong Python tooling, file I/O, and logging practices, with a clear commit contributing to maintainable, scalable data validation.
1 Commits • 1 Features
Dec 1, 2025December 2025: Delivered a robust enhancement to the dynamic-foraging-task data pipeline by extending video frame integrity checks to support both flat and nested folder structures, bolstering data quality and traceability. Implemented improved error handling and logging for frame count discrepancies, enabling reliable monitoring of video data integrity across complex directory layouts. This work reduces manual data curation, improves reproducibility for downstream analyses, and reinforces the project’s data integrity standards. Demonstrated strong Python tooling, file I/O, and logging practices, with a clear commit contributing to maintainable, scalable data validation.
December 2025
September 2025
1 Commits
Sep 1, 2025Month: 2025-09. This month focused on stabilizing the foraging workflow in AllenNeuralDynamics/dynamic-foraging-task by fixing timing parameter misconfigurations and port assignment issues that caused delays. The work directly improved workflow reliability and overall performance, reducing delays in the foraging loop and improving throughput.
September 2025
1 Commits
Sep 1, 2025Month: 2025-09. This month focused on stabilizing the foraging workflow in AllenNeuralDynamics/dynamic-foraging-task by fixing timing parameter misconfigurations and port assignment issues that caused delays. The work directly improved workflow reliability and overall performance, reducing delays in the foraging loop and improving throughput.
May 2025
3 Commits • 1 Features
May 1, 2025May 2025 monthly summary for AllenNeuralDynamics/dynamic-foraging-task focused on code quality improvements and data accuracy in the Foraging module. Targeted cleanup reduced complexity, improved readability, and ensured metadata reflects the actual training state, delivering measurable business value in reliability and maintainability.
3 Commits • 1 Features
May 1, 2025May 2025 monthly summary for AllenNeuralDynamics/dynamic-foraging-task focused on code quality improvements and data accuracy in the Foraging module. Targeted cleanup reduced complexity, improved readability, and ensured metadata reflects the actual training state, delivering measurable business value in reliability and maintainability.
May 2025
April 2025
7 Commits • 4 Features
Apr 1, 2025April 2025 focused on stabilizing and accelerating data capture for AllenNeuralDynamics/dynamic-foraging-task by delivering standardized camera controls, workflow enhancements, and improved data logging and UI layout. These changes increased data quality, reproducibility, and overall experiment throughput.
April 2025
7 Commits • 4 Features
Apr 1, 2025April 2025 focused on stabilizing and accelerating data capture for AllenNeuralDynamics/dynamic-foraging-task by delivering standardized camera controls, workflow enhancements, and improved data logging and UI layout. These changes increased data quality, reproducibility, and overall experiment throughput.
March 2025
1 Commits
Mar 1, 2025Month 2025-03 – Focused on stabilizing the Bonsai-based workflow for the AllenNeuralDynamics/dynamic-foraging-task repository, delivering reliability improvements and UI polish that reduce operational risk and improve data-processing consistency.
1 Commits
Mar 1, 2025Month 2025-03 – Focused on stabilizing the Bonsai-based workflow for the AllenNeuralDynamics/dynamic-foraging-task repository, delivering reliability improvements and UI polish that reduce operational risk and improve data-processing consistency.
March 2025
January 2025
4 Commits • 1 Features
Jan 1, 2025January 2025 highlights for AllenNeuralDynamics/dynamic-foraging-task: Delivered explicit user-stop control and clarified dialog flow to improve experiment governance; fixed critical edge-case in voltage logic by forcing input_voltage to 0 when target_power is 0; added a safe default for None project names ('Behavior Platform') to prevent startup initialization errors. These updates enhance operator control, reliability of waveform production, and initialization safety, reducing run failures and enabling more reproducible experiments. Commits of note include 5439cba..., 6cc4bca..., ffa6fca..., fc4d5e4a... and related changes across the feature/bug fixes.
January 2025
4 Commits • 1 Features
Jan 1, 2025January 2025 highlights for AllenNeuralDynamics/dynamic-foraging-task: Delivered explicit user-stop control and clarified dialog flow to improve experiment governance; fixed critical edge-case in voltage logic by forcing input_voltage to 0 when target_power is 0; added a safe default for None project names ('Behavior Platform') to prevent startup initialization errors. These updates enhance operator control, reliability of waveform production, and initialization safety, reducing run failures and enabling more reproducible experiments. Commits of note include 5439cba..., 6cc4bca..., ffa6fca..., fc4d5e4a... and related changes across the feature/bug fixes.
December 2024
16 Commits • 2 Features
Dec 1, 2024December 2024 – Monthly work summary for AllenNeuralDynamics/dynamic-foraging-task. Highlights include delivered features to the foraging workflow with Bonsai integration improvements, stability and logging improvements for Bonsai configuration, and robust optical tagging metadata handling and processing. These changes improve experiment configuration reliability, data integrity, and user experience, enabling faster experimentation and higher quality data pipelines.
16 Commits • 2 Features
Dec 1, 2024December 2024 – Monthly work summary for AllenNeuralDynamics/dynamic-foraging-task. Highlights include delivered features to the foraging workflow with Bonsai integration improvements, stability and logging improvements for Bonsai configuration, and robust optical tagging metadata handling and processing. These changes improve experiment configuration reliability, data integrity, and user experience, enabling faster experimentation and higher quality data pipelines.
December 2024
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for AllenNeuralDynamics/dynamic-foraging-task: Delivered integration of Running Wheel Data Recording and Encoder/Video Capture in the Bonsai workflow, including data stream configuration, port name standardization, and adjusted delay timings. This enables synchronized behavioral and video/encoder data capture in experiments, improving data fidelity and experimental throughput. Implemented with focused commit: 303ac3dd8590e2073183c9167d5650f32455ef8c.
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for AllenNeuralDynamics/dynamic-foraging-task: Delivered integration of Running Wheel Data Recording and Encoder/Video Capture in the Bonsai workflow, including data stream configuration, port name standardization, and adjusted delay timings. This enables synchronized behavioral and video/encoder data capture in experiments, improving data fidelity and experimental throughput. Implemented with focused commit: 303ac3dd8590e2073183c9167d5650f32455ef8c.
Activity
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Quality Metrics
Correctness81.8%
Maintainability83.6%
Architecture75.8%
Performance79.4%
AI Usage20.6%
Skills & Technologies
Programming Languages
BonsaiC#CSVPythonXML
Technical Skills
Back-end DevelopmentBackend DevelopmentBehavioral ProgrammingCamera IntegrationCode OrganizationCode RefactoringConfiguration ManagementConflict ResolutionControl SystemsData AcquisitionData LoggingData ProcessingEmbedded SystemsError HandlingException Handling
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