I’m a full-stack developer specializing in digital healthcare. With dual majors in optometry/opticianry and computer engineering, I bring interdisciplinary expertise across both fields.

I work end-to-end—from planning and UX/design to development, deployment, and operations—taking ownership of the entire journey from problem definition to solution design to productization.

A platform that digitizes optical shop operations, replacing manual workflows with
a fully integrated system featuring a digital prescription chart and an AI-powered myopia prediction model.
This project was planned, architected, designed, developed, deployed, and operated entirely solo (end-to-end).

• TypeScript-based monorepo (server / front / ai) for unified management
• Flexible Node.js architecture:
  • Shifted from 3-layer (Controller–Service–Repository) to
    2-layer (Controller–Service) depending on development needs
• Improved code consistency and overall development productivity

• Stateless authentication using JWT + HttpOnly cookies
• Implemented Two-Factor Authentication (2FA)
• Designed refresh-token management for multi-device concurrent sessions

• Optimized AWS EC2 Free Tier resource usage
• Integrated AI model training and Python ETL into the CI/CD pipeline
• Operated three WAS servers on a single EC2 instance

• Built a MongoDB → Python ETL pipeline
• Developed an XGBoost-based time-series myopia prediction model
• Provided a FastAPI prediction API (JSON) for real-time inference

A system designed to centralize and streamline scattered maritime regulations and
internal rule documents, providing workflow automation and robust document lifecycle management.

• Designed and implemented an electronic approval workflow for regulation changes
• Automated approval processes to reduce manual oversight

• Implemented CKEditor-based web document editing for complex maritime regulations
• Enabled full online creation, editing, and management of regulatory documents

• Added new/old regulation comparison functionality
• Designed file versioning schemas to strengthen change-history tracking

• Improved large-scale document search using MongoDB Atlas + custom search algorithms
• Achieved near real-time search response for thousands of documents

• Migrated the entire legacy JavaScript codebase to TypeScript
• Significantly improved maintainability and runtime stability

• Backend: Node.js(Express), Nest.js, Python(FastAPI)
• Frontend: React(Vite), Nextjs, Zustand, TanStack Query
• Database: MongoDB (Mongoose), PostgreSQL (with TimescaleDB)
• DevOps: AWS (Route53, Load Balancer, EC2, S3, CloudFront, Amplify), Git Actions, Nginx
• AI & Data: Pandas, Scikit-learn, XGBoost

"Building a better world through efficient code."

• LinkedIn
• Email: dnqkr18@gmail.com