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VBearCode

PROFILE

Vbearcode

Over three months, 23020170@vnu.edu.vn developed and enhanced core features for the ISE-UET-AutoML/frontend repository, focusing on user authentication, dataset management, and application generation from machine learning models. They implemented robust API integration and React-based UI components to streamline multi-step workflows, improve error handling, and support file uploads to AWS S3. Their work included refining dataset search, filter, and sort capabilities, as well as introducing end-to-end functionality for generating deployable apps from ML outputs. Using JavaScript, TypeScript, and Ant Design, they delivered well-structured, maintainable code that improved data integrity, user experience, and the reliability of frontend data operations.

Overall Statistics

Feature vs Bugs

86%Features

Repository Contributions

17Total
Bugs
1
Commits
17
Features
6
Lines of code
6,768
Activity Months3

Work History

January 2026

1 Commits • 1 Features

Jan 1, 2026

January 2026: End-to-end delivery of the Generated Applications from Machine Learning Models feature in ISE-UET-AutoML/frontend, including API endpoints and UI components, enabling users to generate, list, and create apps directly from ML models.

September 2025

4 Commits • 1 Features

Sep 1, 2025

Month: 2025-09 — Frontend (ISE-UET-AutoML/frontend) delivered a focused Dataset Management Page upgrade, combining enhanced search, filter, and sort with a UI refresh and pagination improvements. This work improves dataset discoverability, reduces time to locate datasets, and strengthens data curation workflows. Notable commits include search, filter/sort enhancements, pagination position fix, and header/spacing refinements.

July 2025

12 Commits • 4 Features

Jul 1, 2025

July 2025 performance summary for frontend delivery focused on user experience, data workflow reliability, and observability. Delivered major enhancements across authentication, data export, labeling workflows, and payload debugging. Improvements reduce login friction, ensure robust API responses, and increase data integrity across S3 exports and CSV metadata handling. Strengthened multi-step dataset/label project creation with better metadata support and naming conventions, plus instrumentation to facilitate troubleshooting of payload flows.

Activity

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Quality Metrics

Correctness81.8%
Maintainability81.2%
Architecture74.0%
Performance70.6%
AI Usage23.4%

Skills & Technologies

Programming Languages

JSXJavaScriptReactTypeScript

Technical Skills

API IntegrationAPI integrationAWS S3Ant DesignAsynchronous ProgrammingComponent RefactoringData OrganizationData ProcessingDebuggingError HandlingFile UploadForm HandlingFrontend DevelopmentJavaScriptModal Components

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

ISE-UET-AutoML/frontend

Jul 2025 Jan 2026
3 Months active

Languages Used

JSXJavaScriptReactTypeScript

Technical Skills

API IntegrationAWS S3Ant DesignAsynchronous ProgrammingComponent RefactoringData Organization

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