gem/oq-engine
Nov 2025 – Apr 2026
4 Months active
Languages Used
PythonTextYAMLCSVplaintext
Technical Skills
Pythondata analysismachine learningmodel deploymentsoftware testingproject management
Amir
PROFILE
Amir
Contributed to the gem/oq-engine repository by developing and deploying machine learning-based ground-motion models for regions such as Turkiye and the Azores, integrating XGBoost and ONNX for efficient hazard estimation and cross-platform deployment. Applied Python and scientific computing techniques to refactor model code, optimize inference workflows, and enhance data handling. Improved repository hygiene through documentation updates, contributor attribution, and removal of extraneous files. Addressed API prediction bugs and restored workflow notifications to maintain reliability. The work emphasized reproducible data assets, robust testing, and maintainable code, supporting more accurate seismic risk assessments and streamlined model refresh cycles within the project.
Overall Statistics
Feature vs Bugs
70%Features
Repository Contributions
24Total
Bugs
3
Commits
24
Features
7
Lines of code
1,859
Activity Months4
Your Network
34 peopleShared Repositories
34
Antonio EttorreMember
Anirudh RaoMember
hascarMember
poudelasthaMember
CatalinaYepesMember
Catarina CostaMember
unknownMember
ClaudiaMember
MaoxinWangMember
Work History
April 2026
14 Commits • 3 Features
Apr 1, 2026Concise monthly summary for 2026-04 focusing on key accomplishments, major bug fixes, and business impact for gem/oq-engine. Highlights include ML-driven hazard modeling deployment with Azores GSIM, data assetization via ONNX support, and code/docs hygiene improvements. Example-driven commits supported the work with verification tests and documentation alignment.
14 Commits • 3 Features
Apr 1, 2026Concise monthly summary for 2026-04 focusing on key accomplishments, major bug fixes, and business impact for gem/oq-engine. Highlights include ML-driven hazard modeling deployment with Azores GSIM, data assetization via ONNX support, and code/docs hygiene improvements. Example-driven commits supported the work with verification tests and documentation alignment.
April 2026
January 2026
8 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for gem/oq-engine focusing on key features delivered, major bugs fixed, overall impact, and technologies demonstrated. Summary of work includes ONNX packaging and session management improvements, a class-based refactor of Mohammadi2023Turkiye, Slack notification restoration, and repository cleanup, all contributing to faster inference, greater reliability, maintainability, and cleaner CI/docs.
January 2026
8 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for gem/oq-engine focusing on key features delivered, major bugs fixed, overall impact, and technologies demonstrated. Summary of work includes ONNX packaging and session management improvements, a class-based refactor of Mohammadi2023Turkiye, Slack notification restoration, and repository cleanup, all contributing to faster inference, greater reliability, maintainability, and cleaner CI/docs.
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 (Month: 2025-12) milestones for gem/oq-engine: Delivered contributor attribution improvement by updating the CONTRIBUTORS list to acknowledge Amirhossein Mohammadi's contributions. This metadata-focused change enhances governance, transparency, and onboarding. No code changes affecting functionality or user-facing features were released this month; no major bug fixes were recorded. Impact: improved attribution records, easier audit trails, and stronger collaboration signals; supportive groundwork for governance and compliance. Technologies/skills demonstrated: Git version control, precise commit messaging, contributor governance, metadata management, and documentation hygiene.
1 Commits • 1 Features
Dec 1, 2025December 2025 (Month: 2025-12) milestones for gem/oq-engine: Delivered contributor attribution improvement by updating the CONTRIBUTORS list to acknowledge Amirhossein Mohammadi's contributions. This metadata-focused change enhances governance, transparency, and onboarding. No code changes affecting functionality or user-facing features were released this month; no major bug fixes were recorded. Impact: improved attribution records, easier audit trails, and stronger collaboration signals; supportive groundwork for governance and compliance. Technologies/skills demonstrated: Git version control, precise commit messaging, contributor governance, metadata management, and documentation hygiene.
December 2025
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for gem/oq-engine: Delivered ML-based Turkiye ground-motion model integration using XGBoost, integrated with OpenQuake, including data handling, ONNX model support, and comprehensive testing and documentation. The work enables Turkiye-specific hazard estimation with portable deployability via ONNX and improves model refresh workflows. No major bugs recorded in this scope. Business impact includes sharper risk assessments for Turkiye projects, faster deployment of updated GSIM models, and stronger alignment with OpenQuake capabilities. Technologies demonstrated include machine learning (XGBoost), ONNX, data engineering, testing, OpenQuake integration, and thorough documentation.
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for gem/oq-engine: Delivered ML-based Turkiye ground-motion model integration using XGBoost, integrated with OpenQuake, including data handling, ONNX model support, and comprehensive testing and documentation. The work enables Turkiye-specific hazard estimation with portable deployability via ONNX and improves model refresh workflows. No major bugs recorded in this scope. Business impact includes sharper risk assessments for Turkiye projects, faster deployment of updated GSIM models, and stronger alignment with OpenQuake capabilities. Technologies demonstrated include machine learning (XGBoost), ONNX, data engineering, testing, OpenQuake integration, and thorough documentation.
Activity
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Quality Metrics
Correctness99.2%
Maintainability94.2%
Architecture97.6%
Performance93.4%
AI Usage26.8%
Skills & Technologies
Programming Languages
CSVPythonTextYAMLplaintext
Technical Skills
CI/CDData ModelingData ProcessingDevOpsGitHub ActionsMachine LearningModel OptimizationPythonPython programmingSoftware DevelopmentTestingdata analysisdata managementdata processingdocumentation
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline