taosdata/TDengine
Apr 2026 – May 2026
2 Months active
Languages Used
PythonSQL
Technical Skills
Python programmingSQLanomaly detectiondata analysismachine learningFlask
Haojun Liao
PROFILE
Haojun Liao
Contributed to the taosdata/TDengine repository by developing and enhancing backend analytics features over a two-month period. Delivered a multivariate Local Outlier Factor anomaly detection system supporting multiple numeric features and 2-D result visualization, with careful attention to state management and documentation quality. Improved profile matching accuracy by refining overlap-based filtering logic and integrating TDgpt v3.0, which included updates to service management and anomaly detection workflows. Applied Python, SQL, and Flask to implement robust algorithm design, data analysis, and unit testing practices. Collaborated across teams, addressed edge cases, and ensured code reliability through test-driven development and continuous integration.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
3
Lines of code
6,235
Activity Months2
Your Network
88 peopleShared Repositories
88
Work History
May 2026
2 Commits • 2 Features
May 1, 2026May 2026 TDengine update: delivered feature enhancements and system integration for improved profile matching and reliability. Key accomplishments include: Profile Search Overlap Filtering Enhancement replacing 'exclude_contained' with 'exclude_overlap' to tighten overlap-based filtering; extensive test updates and fixes (including edge-case handling for single-point windows) and app.py adjustments. TDgpt v3.0 Integration merged into main, bringing taosanode configuration, service management improvements, and enhanced anomaly detection. Together, these changes improve matching accuracy, system reliability, and analytics capabilities, while reflecting strong code quality and cross-team collaboration. Commits highlighting the work include 4f4e0e82c4f4e14ddcb61bae62ca82ce9ada41ee and 7bb2547d35ae12f1024d7abd880ab2218e097108.
2 Commits • 2 Features
May 1, 2026May 2026 TDengine update: delivered feature enhancements and system integration for improved profile matching and reliability. Key accomplishments include: Profile Search Overlap Filtering Enhancement replacing 'exclude_contained' with 'exclude_overlap' to tighten overlap-based filtering; extensive test updates and fixes (including edge-case handling for single-point windows) and app.py adjustments. TDgpt v3.0 Integration merged into main, bringing taosanode configuration, service management improvements, and enhanced anomaly detection. Together, these changes improve matching accuracy, system reliability, and analytics capabilities, while reflecting strong code quality and cross-team collaboration. Commits highlighting the work include 4f4e0e82c4f4e14ddcb61bae62ca82ce9ada41ee and 7bb2547d35ae12f1024d7abd880ab2218e097108.
May 2026
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 (TDengine): Delivered multivariate Local Outlier Factor (LoF) anomaly detection with multi-feature support, refined result drawing for 2-D inputs, and cleaned up documentation and code structure. Implemented state management to prevent leakage of prior input data and stabilized the feature for broader production use. This work enhances TDengine's analytics capabilities by enabling robust cross-feature anomaly detection on time-series data and improves developer experience through better documentation and reliability.
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 (TDengine): Delivered multivariate Local Outlier Factor (LoF) anomaly detection with multi-feature support, refined result drawing for 2-D inputs, and cleaned up documentation and code structure. Implemented state management to prevent leakage of prior input data and stabilized the feature for broader production use. This work enhances TDengine's analytics capabilities by enabling robust cross-feature anomaly detection on time-series data and improves developer experience through better documentation and reliability.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage73.4%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
FlaskPythonPython programmingSQLalgorithm designanomaly detectionbackend developmentdata analysismachine learningunit testing
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