Edward Vuong
I’m Edward Vuong, a Master of Computer and Information Science student at AUT with hands-on experience building production-focused applications across back-end, front-end, and AI/ML.
About
I’m Edward Vuong, a Master of Computer and Information Science student at AUT with hands-on experience building production-focused applications across back-end, front-end, and AI/ML. I enjoy turning complex problems into working systems—whether that’s designing RESTful APIs, shipping responsive mobile experiences, or integrating modern AI capabilities using Python, PyTorch, OpenCV, and the Gemini API.
Recently, I’ve been working on real-time, edge-optimized computer vision for robotics, including facial and gesture tracking, and I’ve also developed a gym management app for 100+ members using the MERN stack. I thrive in Agile teams, communicate clearly about trade-offs, and continuously improve performance, reliability, and user experience—always aiming for scalable solutions that can be used in the real world.
- 1 year's experience
- Joined September 2026
Industry experience
- Computers & Electronics
- Software & Internet
- Education
- Healthcare
- Gaming
- Professional Services
Work experience
Scaled a Flask-based humanoid control dashboard for the Unitree G1 by 40% using Windsurf workflows. Built real-time computer vision streaming for facial and gesture tracking at 60 FPS, reducing command latency by 99% for interactive live robot greetings. Implemented MediaPipe-based pose tracking to control the robot’s arm/hand in real time from camera input, coordinating with the research team by communicating progress and technical trade-offs clearly. Focused on performance, responsiveness, and practical engineering constraints for a live robotic system.
Developed a cross-platform gym management mobile application using the MERN stack (React Native, JavaScript/TypeScript, MongoDB, Node.js). Implemented real-time booking and availability checking, reducing scheduling conflicts by 45% via instant database synchronization. Built community features supporting 100+ active members on both Android and iOS, incorporating user feedback through iterative improvements. Collaborated in an Agile environment across UI development, API integration, and feature testing across multiple releases.
Education
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