mne-tools/mne-python
Jul 2025 – Feb 2026
2 Months active
Languages Used
Python
Technical Skills
3D RenderingData VisualizationScientific ComputingSoftware DevelopmentPythondata processing
Victor Férat
PROFILE
Victor Férat
Contributed to the mne-tools/mne-python repository by developing advanced visualization and data processing features for scientific computing workflows. Built 3D source space and BEM visualizations within the MNE-Python Report, refining coordinate frames and view configurations to improve data interpretability for researchers. Enhanced scalp surface generation by introducing an optional reuse_seghead parameter, allowing users to efficiently reuse or recompute segmentation files and reducing the risk of stale results. Leveraged Python for both 3D rendering and data processing, collaborating through GitHub pull requests and maintaining code quality with pre-commit checks. The work emphasized reliability, reproducibility, and user-facing clarity in scientific reporting.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
516
Activity Months2
Your Network
56 peopleShared Repositories
56
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Shristi BaralMember
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Ben TangMember
Bhargav KowshikMember
Britta WestnerMember
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 (2026-02) – Key achievements in mne-python focused on scalp surface generation reliability and efficiency. Delivered an optional reuse of segmentation files via a new reuse_seghead parameter for make_scalp_surfaces, addressing issues with stale assets and reducing recomputation. Fixed a bug in make_scalp_surfaces (Fixes make_scalp_surfaces (#13024)) with commit a5bf268a1a8645a6b4addc467dec70eb0ec26ce3, improving correctness and workflow stability. Overall impact: reduced risk of stale segmentation, faster generation, and better reproducibility for users. Technologies/skills demonstrated: Python parameterization, segmentation workflows, GitHub collaboration (PRs/commit references), and code quality practices (pre-commit-ci, co-authored commits).
1 Commits • 1 Features
Feb 1, 2026February 2026 (2026-02) – Key achievements in mne-python focused on scalp surface generation reliability and efficiency. Delivered an optional reuse of segmentation files via a new reuse_seghead parameter for make_scalp_surfaces, addressing issues with stale assets and reducing recomputation. Fixed a bug in make_scalp_surfaces (Fixes make_scalp_surfaces (#13024)) with commit a5bf268a1a8645a6b4addc467dec70eb0ec26ce3, improving correctness and workflow stability. Overall impact: reduced risk of stale segmentation, faster generation, and better reproducibility for users. Technologies/skills demonstrated: Python parameterization, segmentation workflows, GitHub collaboration (PRs/commit references), and code quality practices (pre-commit-ci, co-authored commits).
February 2026
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for mne-tools/mne-python: Focused on enhancing visualization capabilities in the MNE-Python Report by introducing Source Space Visualizations with precise coordinate frames and configurable views, delivering improved analytics visualization for researchers. This work enhances data interpretability and reporting quality, bridging technical depth with user-facing clarity.
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for mne-tools/mne-python: Focused on enhancing visualization capabilities in the MNE-Python Report by introducing Source Space Visualizations with precise coordinate frames and configurable views, delivering improved analytics visualization for researchers. This work enhances data interpretability and reporting quality, bridging technical depth with user-facing clarity.
Activity
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Quality Metrics
Correctness95.0%
Maintainability80.0%
Architecture85.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
3D RenderingData VisualizationPythonScientific ComputingSoftware Developmentdata processingscientific computing
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