Summary
Jenhao Yang is a Machine Learning Engineer with nine years of experience building real-time computer vision systems, specializing in edge inference using NVIDIA DeepStream, YOLO/Darknet, and C++/Python. He designs end-to-end pipelines—annotation platforms, model-assisted tooling, Dockerized training and FastAPI deployment—to turn camera streams into real-time people and traffic analytics and ELK alerts. Notable achievements include migrating annotation workflows to a collaborative CVAT platform and building a plugin to read Darknet weights, significantly accelerating labeler throughput. He also led a lung nodule CT detection POC, owning data cleaning, preprocessing, training and monitoring with TensorBoard. Comfortable applying software design patterns (Strategy, Observer, State) and multiprocessing for scalable, maintainable systems, Jenhao blends low-level performance tuning with practical ML operations on Ubuntu and edge hardware. Based in Taipei, he brings a pragmatic focus on maximizing recognition speed and deployment robustness for production AI applications.
9 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Mechanical Engineering, Bachelor's degree, Mechanical Engineering at Chang Gung University
Master's degree, Mechanical Engineering, Master's degree, Mechanical Engineering at National Taiwan University of Science and Technology