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, Janghanpyeong developed and stabilized a hyperspectral imaging machine learning pipeline in the JANGHANPYEONG/20252R0136COSE48002 repository, focusing on modularity and reproducibility. He implemented band selection for 3D-CNNs, added configurable model architectures like HSI_PLSR and SSANet, and introduced attention module controls to support flexible inference. In August, he expanded the backend with a scalable data API stack, migrating services to FastAPI and reinforcing database resilience through health checks and mock data fallbacks. Using Python, PyTorch, and SQLAlchemy, his work addressed both model development and robust data handling, demonstrating depth in both machine learning and backend engineering.
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 people
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
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