Frontend Development: Engineered a reusable Vue.js TimelineMarker component for video players, providing role-based navigation and visually indicating question status to enhance learning path clarity and content management. Performance Optimization: Diagnosed and resolved Flash of Unstyled Text (FOUT) issues by implementing SVG-based icon libraries and optimizing font loading, achieving a 75% font payload reduction and improving first-paint latency by 150ms. Backend & Database: Refactored the PostgreSQL data model to link questions with precise video timestamps and developed Express.js APIs to track student progress and enforce sequential viewing restrictions, fulfilling key stakeholder requirements for interactive content creation.

AI-Powered Tutor Platform: Contributed to developing an interactive video lesson system with a 3D virtual avatar, reducing content creation time by 30%. Backend Development: Assisted in building a scalable backend using Python and Django REST Framework, implementing the MVT pattern for structured data handling. Intelligent Chatbot (RAG): Helped develop and integrate a Retrieval-Augmented Generation chatbot, improving student engagement by 20%. Automated Video Processing: Developed an automation pipeline to convert PDF-based content into interactive videos, cutting production time by 50%. 3D Avatar Integration: Implemented Vue.js and Three.js to support video-based lesson delivery with lifelike avatars, aligning gestures with Whisper V3 audio for natural synchronization. Cross-Functional Collaboration: Worked closely with design, QA, and product teams to resolve issues and enhance feature quality.

Insurance Data Automation: Designed and implemented Python scripts to replace manual data entry, reducing processing time by 40% and minimizing errors. Automated News Retrieval: Developed a Python-based Selenium scraper to extract daily financial news from IgnitesAsia, automatically emailing reports to management and reducing monitoring effort by 80%.