FAIR-Chem/fairchem
Nov 2024 – Jan 2026
3 Months active
Languages Used
MarkdownJinjaPythonYAML
Technical Skills
DocumentationNeural Network DesignPyTorchRelease ManagementSpherical HarmonicsUnit Testing
Anuroop Sriram
PROFILE
Anuroop Sriram
Anuroop S. contributed to the FAIR-Chem/fairchem repository by developing and integrating features that enhanced both usability and reliability for direct air capture simulations. He updated model checkpoint documentation and dataset links using Markdown and YAML, improving user access to pretrained models. Leveraging Python and PyTorch, he released the ODAC25 dataset and models, deprecated outdated versions, and expanded unit tests for neural network modules such as EquivariantNorm and MOLE. His work included creating a dedicated ODAC data handling package, streamlining data workflows and reducing manual preparation. These efforts improved documentation clarity, test coverage, and the maintainability of the codebase.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
4
Lines of code
1,583
Activity Months3
Your Network
338 people
Work History
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for FAIR-Chem/fairchem: Key feature delivery and stable performance across the DAC workflow. Delivered ODAC25 model integration into the pretrained models and established a dedicated ODAC data handling package to streamline direct air capture simulations. The work reduces manual data prep, accelerates experimentation, and improves simulation fidelity for DAC scenarios. No major bugs fixed this month; observed harmonization with existing pipelines and documentation updates. Commit 26c8f24111958f3d173f0099142758506c8115fa documents the changes under #1719.
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for FAIR-Chem/fairchem: Key feature delivery and stable performance across the DAC workflow. Delivered ODAC25 model integration into the pretrained models and established a dedicated ODAC data handling package to streamline direct air capture simulations. The work reduces manual data prep, accelerates experimentation, and improves simulation fidelity for DAC scenarios. No major bugs fixed this month; observed harmonization with existing pipelines and documentation updates. Commit 26c8f24111958f3d173f0099142758506c8115fa documents the changes under #1719.
January 2026
August 2025
3 Commits • 2 Features
Aug 1, 2025Monthly work summary for 2025-08 focusing on delivering core platform capabilities and improving test coverage in FAIR-Chem/fairchem.
August 2025
3 Commits • 2 Features
Aug 1, 2025Monthly work summary for 2025-08 focusing on delivering core platform capabilities and improving test coverage in FAIR-Chem/fairchem.
November 2024
1 Commits • 1 Features
Nov 1, 2024In November 2024, the FAIR-Chem/fairchem repository delivered a focused documentation improvement for ODAC checkpoints and maintained high-quality standards. Key feature delivered: ODAC Checkpoint Documentation Update, updating the model_checkpoint documentation to reflect new checkpoint file names and updated links in the ODAC dataset markdown, which improves user findability of pretrained models. Major bugs fixed: none reported this month; the work prioritized documentation accuracy and discoverability. Overall impact: enhanced usability and quicker access to pretrained models, supporting faster experimentation, onboarding, and user satisfaction. Technologies/skills demonstrated: markdown documentation, version control with clear and traceable commits, link maintenance, and alignment with dataset documentation practices.
1 Commits • 1 Features
Nov 1, 2024In November 2024, the FAIR-Chem/fairchem repository delivered a focused documentation improvement for ODAC checkpoints and maintained high-quality standards. Key feature delivered: ODAC Checkpoint Documentation Update, updating the model_checkpoint documentation to reflect new checkpoint file names and updated links in the ODAC dataset markdown, which improves user findability of pretrained models. Major bugs fixed: none reported this month; the work prioritized documentation accuracy and discoverability. Overall impact: enhanced usability and quicker access to pretrained models, supporting faster experimentation, onboarding, and user satisfaction. Technologies/skills demonstrated: markdown documentation, version control with clear and traceable commits, link maintenance, and alignment with dataset documentation practices.
November 2024
Activity
Loading activity data...
Quality Metrics
Correctness96.0%
Maintainability96.0%
Architecture96.0%
Performance92.0%
AI Usage28.0%
Skills & Technologies
Programming Languages
JinjaMarkdownPythonYAML
Technical Skills
DocumentationNeural Network DesignPyTorchPythonRelease ManagementSpherical HarmonicsUnit Testingdata sciencemachine learningsoftware development
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline