JANGHANPYEONG/20252R0136COSE48002
Jul 2025 – Aug 2025
2 Months active
Languages Used
BinaryJSONPythonSQLYAML
Technical Skills
Artifact ManagementBackend DevelopmentCode RefactoringComputer VisionConfiguration ManagementData Analysis
potato
PROFILE
Potato
Over two months, contributed to the JANGHANPYEONG/20252R0136COSE48002 repository by building and refining a hyperspectral imaging machine learning pipeline and delivering scalable data services. Developed features such as band selection for 3D-CNNs, an MLP Fusion module for dimensionality reduction, and integrated new models including HSI_PLSR and SSANet with configuration-driven workflows. Migrated core APIs from Flask to FastAPI, modularized backend utilities, and enhanced database resilience with health checks and mock data fallback. Leveraged Python, PyTorch, and SQLAlchemy to strengthen maintainability, reproducibility, and performance, while resolving 17 bugs and implementing 20 features to support rapid iteration and business reliability.
Overall Statistics
Feature vs Bugs
54%Features
Repository Contributions
78Total
Bugs
17
Commits
78
Features
20
Lines of code
29,449
Activity Months2
Your Network
9 peopleShared Repositories
9
Work History
August 2025
44 Commits • 13 Features
Aug 1, 2025August 2025 highlights for JANGHANPYEONG/20252R0136COSE48002: focused on delivering scalable data services, stabilizing core modules, and strengthening maintainability to support rapid feature cadence and business reliability. Key work spanned implementing an MLP Fusion module for dimensionality reduction, modernizing the API layer, establishing a robust data API stack, reinforcing DB resilience, and expanding data tooling.
44 Commits • 13 Features
Aug 1, 2025August 2025 highlights for JANGHANPYEONG/20252R0136COSE48002: focused on delivering scalable data services, stabilizing core modules, and strengthening maintainability to support rapid feature cadence and business reliability. Key work spanned implementing an MLP Fusion module for dimensionality reduction, modernizing the API layer, establishing a robust data API stack, reinforcing DB resilience, and expanding data tooling.
August 2025
July 2025
34 Commits • 7 Features
Jul 1, 2025July 2025 monthly performance summary for JANGHANPYEONG/20252R0136COSE48002. Focus was on enhancing the hyperspectral imaging ML pipeline, expanding the model portfolio, and strengthening reproducibility through config-driven workflows.
July 2025
34 Commits • 7 Features
Jul 1, 2025July 2025 monthly performance summary for JANGHANPYEONG/20252R0136COSE48002. Focus was on enhancing the hyperspectral imaging ML pipeline, expanding the model portfolio, and strengthening reproducibility through config-driven workflows.
Activity
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Quality Metrics
Correctness79.8%
Maintainability81.2%
Architecture75.6%
Performance69.2%
AI Usage21.6%
Skills & Technologies
Programming Languages
BinaryJSONPythonSQLYAML
Technical Skills
API DevelopmentArtifact ManagementBackend DevelopmentCode RefactoringComputer VisionConfiguration ManagementData AnalysisData HandlingData ModelingData PreprocessingData ProcessingData ScienceDatabase IntegrationDatabase InteractionDatabase Management
Repositories Contributed To
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