Yong Kheng Beh

Key Achievements

• Platform Migration: Building on an initial foundation from a contract team, completed the migration of the production app from Firebase (Firestore, Cloud Functions, Hosting) to Next.js, Supabase (Postgres) and Vercel as the sole engineer. V2 is now live and the Firebase version has been retired.

• Website Redevelopment: Designed and built the new vocare.com.au on my own, replacing a single static HTML page with a Next.js, React and TypeScript site on Vercel, backed by unit and end-to-end tests.

• Production Ownership: Own the platform end to end — features, database schema changes, CI, error monitoring, and dependency security patches.

• Accessibility: Remediated the marketing site against WCAG 2.2 AA across theme, navigation, motion and forms.

• Agentic Engineering: Deliver full-stack work solo with Claude Code inside a disciplined workflow of tests, reviews and codebase audits — the subject of my talk at the Adelaide Claude Code Meetup.

Key Achievements

• Solo Rebuild: Returned in March 2026 and rebuilt the site on a clean Drupal 11 codebase on my own, including a redesign of the website.

• Streamlined Migration: Combined the data-cleansing Python scripts and Drupal Migration YAML into one streamlined, repeatable migration process.

• Stakeholder Demo: Demoed the rebuilt site to the not-for-profit, who now want to publish it.

• Gathered and analysed requirements in collaboration with the Directory Manager and Connecting Up leadership to guide redevelopment priorities.

• Created detailed, step-by-step onboarding guides in GitHub and maintained a GitHub Project Kanban board to coordinate the volunteer team.

• Leveraged LLMs (Gemini) to transform unstructured data into structured formats for database integration.

Key Achievements

• Production Maintenance: Fixed a large number of critical bugs in the live app — including mobile layout issues and audio playback errors — to ensure the system ran smoothly for active users.

• Performance Improvements: Reduced cloud costs and improved app speed by setting up caching and optimising Firebase database queries.

• AI-Assisted Development: Leveraged GitHub Copilot to accelerate development — using it to understand undocumented legacy code and rapidly build new features such as workshop reminders and progress bars in React and TypeScript.

• Quality Assurance: Reviewed V2 builds against the existing app so business requirements carried over cleanly to the new platform.

• Process Improvement: Set up a structured bug-logging system on Notion, enabling the CEO and non-technical staff to report issues accurately and improving overall engineering visibility.

Key Achievements

• Annotated coronary angiogram images with high accuracy, leveraging medical training to ensure clinically reliable labels for AI model development.

• Provided structured feedback on annotation software performance, usability, and workflow to help improve tool efficiency and user experience.

• Developed clear annotation guidelines to support new annotators, based on best practices refined through consistent, high-quality annotation work.

Key Achievements

• Cleaned and standardised all datasets collected by the UN Ocean Decade programme over the past five years to improve data quality and usability.

• Designed an interactive data schema and built a relational database to support long-term data management and analysis.

• Documented the full database structure to ensure clarity, maintainability, and smooth handover for future developers.

• Reviewed technical requirements for an upcoming full-stack platform where the database will be integrated.

• Coordinated updates with the broader Ocean Decade Team to validate and align newly received data with the database design.

• Recognised for outstanding performance, strong accountability, and exceptional work ethic throughout the assignment.

Key Achievements

• Developed a Python-based testing framework, automated via shell scripts, to streamline semantic search evaluation — significantly reducing manual testing time.

• Conducted extensive benchmarking with top-ranked embedding models from the MTEB leaderboard on Hugging Face.

• Benchmarked and optimised semantic search performance across multiple vector stores, including OpenSearch.

• Resolved a critical semantic ranking bug — identified cosine distance vs similarity scoring mismatch, significantly improving search accuracy and result relevance.

• Produced comprehensive technical reports to ensure effective knowledge transfer.

Key Achievements

• Led backend development, integrating LangChain for LLM-based tool calls and semantic search — resulting in an Agentic RAG chatbot capable of handling vague human queries with high accuracy.

• Optimised chatbot performance through advanced prompt engineering and retrieval strategies to improve response relevance.

• Deployed the chatbot using Docker, resolving compatibility issues within an outdated software environment.

• Collaborated closely with frontend developers and stakeholders to refine chatbot functionality for real-world use cases.

Key Achievements

• Collaborated with healthcare experts and ML specialists to explore AI-driven decision-making solutions for medical applications.

• Processed and analysed a large-scale healthcare dataset with 6,000+ patient records, developing ML models to predict patient outcomes.

• Researched and reviewed AI-driven predictive analytics in healthcare, integrating insights into model design.

• Presented research findings to a panel of researchers at the end of the internship.