Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull
Feb 2026 – Feb 2026
1 Month active
Languages Used
MATLAB
Technical Skills
MATLABMATLAB scriptingdata analysisdata visualizationexperimental designfile management
David Chung
PROFILE
David Chung
David Chung developed new imaging data analysis capabilities for the Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull repository, focusing on MATLAB scripting for neuroscience workflows. He built a retinotopic mapping script that standardizes two-photon imaging data analysis, improving reproducibility and throughput. David also created a comprehensive OriAnalysis tutorial, guiding users through data loading, orientation tuning analysis, statistical modeling, and visualization. His work included a codebase refactor, removing obsolete files and reorganizing scripts for clarity and maintainability. By emphasizing data analysis, experimental design, and script organization, David’s contributions enhanced onboarding, usability, and long-term reliability for imaging data processing in MATLAB environments.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
2
Lines of code
2,176
Activity Months1
Your Network
10 people
Work History
February 2026
4 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary for Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull: Focused delivery of key imaging data analysis capabilities and usability improvements. Delivered two major features: (1) 2P Imaging Data Analysis - Retinotopic Mapping MATLAB script enabling robust retinotopic mapping workflows, with traceable commits; (2) OriAnalysis Tutorial and Usability Enhancements providing end-to-end guidance for data loading, processing, orientation tuning analysis, statistical testing, plotting tuning curves, and model verification. Also completed Codebase Cleanup and Refactor to remove obsolete cross-orientation experiments files and reorganize/rename scripts for clarity and maintainability. These efforts improve analysis throughput, reproducibility, onboarding, and long-term maintainability, aligning with business goals of reliable, scalable imaging data analysis.
4 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary for Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull: Focused delivery of key imaging data analysis capabilities and usability improvements. Delivered two major features: (1) 2P Imaging Data Analysis - Retinotopic Mapping MATLAB script enabling robust retinotopic mapping workflows, with traceable commits; (2) OriAnalysis Tutorial and Usability Enhancements providing end-to-end guidance for data loading, processing, orientation tuning analysis, statistical testing, plotting tuning curves, and model verification. Also completed Codebase Cleanup and Refactor to remove obsolete cross-orientation experiments files and reorganize/rename scripts for clarity and maintainability. These efforts improve analysis throughput, reproducibility, onboarding, and long-term maintainability, aligning with business goals of reliable, scalable imaging data analysis.
February 2026
Activity
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Quality Metrics
Correctness95.0%
Maintainability95.0%
Architecture95.0%
Performance85.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MATLAB
Technical Skills
MATLABMATLAB scriptingdata analysisdata visualizationexperimental designfile managementimage processingscript organizationstatistical modeling
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