pyg-team/pytorch_geometric
May 2025 – May 2025
1 Month active
Languages Used
MarkdownPython
Technical Skills
3D Data ProcessingDataset IntegrationMachine LearningPyTorch GeometricPython
Juan David Henao
PROFILE
Juan David Henao
Judhen Aosa integrated the MedShapeNet dataset into the pyg-team/pytorch_geometric repository, enabling DGCNN classification workflows to support both ModelNet and MedShapeNet datasets. This work involved 3D data processing and dataset integration using Python and PyTorch Geometric, with a focus on expanding dataset interoperability for machine learning experiments. Judhen updated the DGCNN example to accommodate the new dataset and implemented unit tests to ensure reliability and maintainability. The integration was delivered as a single commit, reflecting a focused and well-scoped contribution. This work broadened the repository’s dataset compatibility and reinforced test-driven development practices within the project’s ecosystem.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
259
Activity Months1
Your Network
112 people
Work History
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for pyg-team/pytorch_geometric: Delivered MedShapeNet dataset integration and DGCNN example/test support, expanding dataset interoperability and testing coverage. No major bugs fixed this month. Impact: broader dataset compatibility enables faster experimentation and adoption; improved test coverage reinforces reliability in model workflows. Technologies/skills demonstrated: dataset integration, test-driven development, PyTorch Geometric ecosystem, and cross-repo collaboration.
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for pyg-team/pytorch_geometric: Delivered MedShapeNet dataset integration and DGCNN example/test support, expanding dataset interoperability and testing coverage. No major bugs fixed this month. Impact: broader dataset compatibility enables faster experimentation and adoption; improved test coverage reinforces reliability in model workflows. Technologies/skills demonstrated: dataset integration, test-driven development, PyTorch Geometric ecosystem, and cross-repo collaboration.
May 2025
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
3D Data ProcessingDataset IntegrationMachine LearningPyTorch GeometricPython
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline