I'm a software engineer with a passion for building full-stack applications and intelligent user experiences. I enjoy working at the intersection of web development, computer vision, and thoughtful UI/UX design -- turning complex technical problems into tools that feel intuitive and useful.
I'm currently seeking opportunities in software engineering, full-stack development, and UX/UI development.
| Category | Technologies |
|---|---|
| Languages | TypeScript, JavaScript, Python, C/C++, HTML, CSS |
| Frontend | React, Bootstrap, Responsive Design |
| Backend | Node.js, Express, Flask, REST API Design |
| Databases | PostgreSQL, Sequelize ORM |
| AI / Computer Vision | MediaPipe, OpenCV, Pose Detection |
| Auth and Security | JWT, bcrypt, Helmet |
| Tools and Platforms | Git, npm, Arduino, Embedded Systems |
A full-stack AI-powered fitness tracking application built with React, TypeScript, Node.js/Express, and PostgreSQL. Uses MediaPipe for real-time pose detection during workouts, with JWT authentication, a tier-based progression system, and Chart.js data visualizations.
A web-based workout pose analyzer combining a React frontend with a Python Flask backend. Leverages MediaPipe and OpenCV to capture and analyze exercise form through joint angle detection, generating configuration files for the Workute fitness platform.
An improved iteration of the workout analyzer with a refactored backend architecture. Separates concerns across dedicated modules for configuration, video processing, and API routing, demonstrating clean code practices and iterative development.
A Python computer vision toolkit for offline workout video analysis. Includes multiple analyzer variants, Excel-to-JSON conversion tools, and a Flask upload API -- built with OpenCV, MediaPipe, Pandas, and NumPy.
A skill-sharing platform UI prototype focused on clean layout, responsive design, and accessible interface patterns. Built with HTML and CSS to explore user-centered design for community-driven skill exchange.
A robotics lab portfolio developed for COGS 300 at UBC. Covers motor control, BLE wireless communication, wall following, line following, Bayesian object tracking, and maze navigation -- built with Arduino C++ and Processing across 6 progressive labs.
I'm always open to collaboration, interesting projects, and new opportunities. Feel free to reach out here on GitHub.