Phạm Nguyễn Hoàng Anh

I’m a Computer Vision Engineer focused on building real-time AI video analytics systems that run reliably in production. I work across the full pipeline—from multi-camera RTSP ingestion to edge/GPU inference optimization and backend deployment.

In my current work (2023–Present), I built a real-time vehicle tracking pipeline using YOLO with RTSP streams and developed an automatic license plate recognition (LPR/ANPR) system. I also integrated OCR and vehicle attribute recognition, then improved multi-stream inference performance for deployment.

I’m experienced in backend and infrastructure that supports real-world operation, including deployment on Ubuntu and AWS EC2 and managing production Linux servers and GitLab CI environments. I’ve worked directly with TensorRT inference engines for accelerated deployment and used Python with Flask/FastAPI to deliver dependable REST APIs.

I bring a practical, systems-minded approach: optimizing performance, improving asynchronous processing with ThreadPoolExecutor, and designing solutions that connect AI perception to operational workflows—such as my Smart Parking System integrating camera-based plate recognition and parking event management.