ISE-UET-AutoML/frontend
Jul 2025 – Jan 2026
6 Months active
Languages Used
CSSJSXJavaScriptReactHTML
Technical Skills
API IntegrationAnt DesignCSV ParsingData VisualizationFrontend DevelopmentJavaScript
thanhvinh0702
PROFILE
Thanhvinh0702
Over six months, Thanh Vinh contributed to the ISE-UET-AutoML/frontend repository by building and enhancing complex frontend features for machine learning model management. He developed interfaces for model deployment, training history, prediction workflows, and real-time monitoring, integrating React and JavaScript with Ant Design and Tailwind CSS for robust UI/UX. His work included dynamic data visualization, support for multiple input modalities such as audio and tabular data, and persistent state management using Zustand. By aligning frontend components with evolving backend APIs and improving data integrity, Thanh Vinh delivered reliable, scalable workflows that improved user experience and operational observability across the platform.
Overall Statistics
Feature vs Bugs
91%Features
Repository Contributions
46Total
Bugs
2
Commits
46
Features
21
Lines of code
53,868
Activity Months6
Your Network
12 people
Work History
January 2026
3 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for ISE-UET-AutoML/frontend focusing on observability, model versioning alignment, and data integrity. Delivered real-time monitoring dashboard with copyable URL and system/GPU monitoring, introduced a Model Versioning API and updated deployed model view for versioning compatibility, and fixed training payload to include train data ID to ensure correct dataset usage. These improvements enhance reliability, reproducibility, and operational insight for deployed models and training workflows, delivering measurable business value and technical robustness.
3 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for ISE-UET-AutoML/frontend focusing on observability, model versioning alignment, and data integrity. Delivered real-time monitoring dashboard with copyable URL and system/GPU monitoring, introduced a Model Versioning API and updated deployed model view for versioning compatibility, and fixed training payload to include train data ID to ensure correct dataset usage. These improvements enhance reliability, reproducibility, and operational insight for deployed models and training workflows, delivering measurable business value and technical robustness.
January 2026
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 — ISE-UET-AutoML/frontend: Delivered Audio Prediction Upload and UI Enhancements, enabling users to upload audio files for model predictions and supporting audio-specific UI features. Improved data handling for predictions and integrated audio workflow into the frontend. No major bugs reported this month. Impact: expanded input modalities for model predictions, improved user workflow and data reliability, setting the stage for broader media support and faster time-to-value for users. Technologies/skills: frontend feature development, UI/UX enhancements, data handling and integration, commit-driven delivery.
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 — ISE-UET-AutoML/frontend: Delivered Audio Prediction Upload and UI Enhancements, enabling users to upload audio files for model predictions and supporting audio-specific UI features. Improved data handling for predictions and integrated audio workflow into the frontend. No major bugs reported this month. Impact: expanded input modalities for model predictions, improved user workflow and data reliability, setting the stage for broader media support and faster time-to-value for users. Technologies/skills: frontend feature development, UI/UX enhancements, data handling and integration, commit-driven delivery.
October 2025
2 Commits • 1 Features
Oct 1, 2025October 2025: Delivered the Prediction History feature in ISE-UET-AutoML/frontend with multi-modal viewing support (images, text, and multi-label predictions), along with improved APIs for data retrieval and display. Also enhanced deployment/upload workflows for managing prediction results. Implemented a targeted fix for prediction versioning by enforcing a dedicated prefix for getNextVersion calls, preventing conflicts with other project versions. These efforts improve data visibility, reliability of predictions, and deployment efficiency, enabling faster iteration and better operational analytics across the product.
2 Commits • 1 Features
Oct 1, 2025October 2025: Delivered the Prediction History feature in ISE-UET-AutoML/frontend with multi-modal viewing support (images, text, and multi-label predictions), along with improved APIs for data retrieval and display. Also enhanced deployment/upload workflows for managing prediction results. Implemented a targeted fix for prediction versioning by enforcing a dedicated prefix for getNextVersion calls, preventing conflicts with other project versions. These efforts improve data visibility, reliability of predictions, and deployment efficiency, enabling faster iteration and better operational analytics across the product.
October 2025
September 2025
16 Commits • 5 Features
Sep 1, 2025September 2025 monthly summary for ISE-UET-AutoML/frontend focusing on delivering end-to-end frontend improvements, expanding task type support, and elevating observability and UX. Highlights include a new Project Info page, support for Time Series and Multilabel Tabular Classification task types, a comprehensive Training/Experiment UI overhaul, deployment status enhancements with real-time updates, and RESTful improvements to the Project Deletion API.
September 2025
16 Commits • 5 Features
Sep 1, 2025September 2025 monthly summary for ISE-UET-AutoML/frontend focusing on delivering end-to-end frontend improvements, expanding task type support, and elevating observability and UX. Highlights include a new Project Info page, support for Time Series and Multilabel Tabular Classification task types, a comprehensive Training/Experiment UI overhaul, deployment status enhancements with real-time updates, and RESTful improvements to the Project Deletion API.
August 2025
7 Commits • 5 Features
Aug 1, 2025Concise monthly summary for 2025-08 highlighting key frontend delivery, stability improvements, and technical accomplishments for ISE-UET-AutoML/frontend. Focused on business value, user experience, and data visualization capabilities.
7 Commits • 5 Features
Aug 1, 2025Concise monthly summary for 2025-08 highlighting key frontend delivery, stability improvements, and technical accomplishments for ISE-UET-AutoML/frontend. Focused on business value, user experience, and data visualization capabilities.
August 2025
July 2025
17 Commits • 7 Features
Jul 1, 2025July 2025 — The frontend delivered key enhancements to the ML deployment lifecycle and training visibility, aligning UI with backend APIs to accelerate model delivery and improve data reliability. Key results include a new Deployed Models UI with deployment navigation, integrated ML Training UI with history and metrics, and enhanced deployment/prediction workflows for multi-task models with dynamic resource handling. Data ingestion for tabular datasets was improved with multi-column configuration and robust column extraction, while training flow UX was strengthened with persistent task management and background processing. UX improvements to multimodal upload navigation and background deployment persistence further reduced user friction and ensured long-running tasks survive reloads. Major bugs fixed included the tabular extraction bug and alignment of the frontend with the new backend API for deployment.
July 2025
17 Commits • 7 Features
Jul 1, 2025July 2025 — The frontend delivered key enhancements to the ML deployment lifecycle and training visibility, aligning UI with backend APIs to accelerate model delivery and improve data reliability. Key results include a new Deployed Models UI with deployment navigation, integrated ML Training UI with history and metrics, and enhanced deployment/prediction workflows for multi-task models with dynamic resource handling. Data ingestion for tabular datasets was improved with multi-column configuration and robust column extraction, while training flow UX was strengthened with persistent task management and background processing. UX improvements to multimodal upload navigation and background deployment persistence further reduced user friction and ensured long-running tasks survive reloads. Major bugs fixed included the tabular extraction bug and alignment of the frontend with the new backend API for deployment.
Activity
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Quality Metrics
Correctness84.6%
Maintainability82.2%
Architecture80.0%
Performance78.0%
AI Usage21.8%
Skills & Technologies
Programming Languages
CSSHTMLJSXJavaScriptReact
Technical Skills
API IntegrationAPI integrationAnt DesignCSSCSV ParsingComponent DevelopmentComponent StylingData VisualizationFrontend DevelopmentJavaScriptLocal StoragePollingReactReact HooksReact Router
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