Machine Learning Engineer with a passion for computer vision, robotics, and understanding how things work at a low level.
🎓 Self-taught in computer science with a mathematics background. I learned everything from the ground up.
🤖 Previously worked at ASUS Robotics & AI Center in Taiwan as a Machine Learning Engineer.
🌏 Fluent in Mandarin Chinese (self-taught).
📊 Started my career as a Data Scientist at HPS Worldwide, designing and implementing machine learning models for credit card fraud detection.
- 👁️ Computer Vision — My primary area of expertise and interest
- 🦾 Robotics — Exploring real-world AI applications through Hugging Face's LeRobot
- ⚡ GPU Programming & Hardware — Understanding the low-level mechanics behind deep learning frameworks
| Project | Description |
|---|---|
| segcam | Real-time semantic segmentation on live camera feeds using YOLOv8-seg, with support for Metal (Apple Silicon), CUDA, and CPU backends. |
| tinygrad-tutos | Tutorials about tinygrad, an end-to-end deep learning stack. A deep dive into how modern ML frameworks work under the hood. |
| mnist-cuda | A simple CUDA-accelerated neural network for MNIST digit classification, built from scratch to understand GPU programming fundamentals. |
| tinygpt | A minimal implementation of GPT architecture using the tinygrad end-to-end deep learning framework. |
授人以魚不如授人以漁。— Better to teach someone to fish than to give him a fish. — Mieux vaut apprendre à pêcher que de donner un poisson.