google-research/weatherbenchX
Nov 2025 – Jan 2026
2 Months active
Languages Used
Python
Technical Skills
Pythondata analysisstatistical modeling
Shreya Agrawal
PROFILE
Shreya Agrawal
Shreyaa contributed to the google-research/weatherbenchX repository by enhancing its model evaluation framework for weather prediction. Over two months, Shreyaa implemented advanced statistical metrics, including the Heidke Skill Score, Equitable Threat Score, and Symmetric Extremal Dependency Index, to provide more nuanced and fair assessments of probabilistic and categorical forecasts. The work involved integrating these metrics into the existing Python-based evaluation pipeline, leveraging data analysis and statistical modeling skills to ensure seamless calculation and reporting. These additions improved the robustness of model comparison and selection, supporting research workflows and enabling more informed decision-making within the weatherbenchX project.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
111
Activity Months2
Your Network
4666 peopleSame Organization
@google.com4654
Benedict OdaiMember
Craig IngramMember
KayyuriMember
Scott SuarezMember
Agent2Agent (A2A) BotMember
Andreas AbelMember
Aadi KapurMember
Aadish GoelMember
Aahil MehtaMember
Work History
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 — Google WeatherBenchX: Delivered the Symmetric Extremal Dependency Index (SEDI) metric integration to enhance evaluation of categorical metrics in weatherbenchX. Commit dc457bc6e78f64abd0cec3d17656a6f53a1870ae (PiperOrigin-RevId: 852400966) implemented the change and ensured traceability. Major bugs fixed: None reported this month. Overall impact: Enables more robust assessment of weather prediction models, improving model selection and research throughput. Technologies demonstrated: metric integration within the evaluation pipeline and Git-based traceability through the dedicated commit.
1 Commits • 1 Features
Jan 1, 2026January 2026 — Google WeatherBenchX: Delivered the Symmetric Extremal Dependency Index (SEDI) metric integration to enhance evaluation of categorical metrics in weatherbenchX. Commit dc457bc6e78f64abd0cec3d17656a6f53a1870ae (PiperOrigin-RevId: 852400966) implemented the change and ensured traceability. Major bugs fixed: None reported this month. Overall impact: Enables more robust assessment of weather prediction models, improving model selection and research throughput. Technologies demonstrated: metric integration within the evaluation pipeline and Git-based traceability through the dedicated commit.
January 2026
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for google-research/weatherbenchX: Focused on strengthening model evaluation capabilities by introducing robust, publication-ready metrics that enhance decision-making around weather prediction models.
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for google-research/weatherbenchX: Focused on strengthening model evaluation capabilities by introducing robust, publication-ready metrics that enhance decision-making around weather prediction models.
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Pythondata analysisstatistical modeling
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