# Shining Yu > Senior Software Engineer at Google Cloud AI Location: San Francisco Bay Area, United States Profile: https://flows.cv/shining I am software engineer at Waymo, building ML-based traffic light perception system . My domain expertise are computer vision and deep learning. ## Work Experience ### Senior Software Engineer, Machine Learning @ Google Jan 2023 – Present | Sunnyvale, California, United States Develop Gemini-powered document parsing pipeline for understanding unstructured data, to empower AI applications such as RAG and Gemini Enterprise. ### Software Engineer, Machine Learning @ Waymo Jan 2021 – Jan 2023 | Mountain View, California, United States Develop deep learning models for traffic light recognition system. ### Capstone Project: Updating HD Maps @ Argo AI Jan 2020 – Jan 2020 | Pittsburgh ### Intern, Perception Research and Development @ Waymo Jan 2020 – Jan 2020 ### Research Assistant at Learning & Vision Lab @ National University of Singapore Jan 2018 – Jan 2019 Part-time Research Assistant advised by Professor Feng Jiashi Ÿ Designed a speed-efficient algorithm to simulate optical flow features from motion vectors in compressed videos Ÿ Improved compressed video action recognition pipeline with the designed algorithm Ÿ Summarized our work in my undergraduate thesis paper ### Research Assistant at Rapid-Rich Object Search Lab @ Nanyang Technological University Jan 2017 – Jan 2018 | Singapore Part-time Research Assistant advised by Professor Yuan Junsong Project: Players and Ball Tracking From Multi-Camera Soccer Videos Ÿ Performed camera calibration for the multicamera system Ÿ Re-implemented probability occupancy map for multicamera tracking Ÿ Redesigned the gridding used in probability occupancy map and improved performance ### Reaserch Internship at Singapore R&D Center Learning & Vision Group @ Panasonic Jan 2017 – Jan 2018 | Singapore Project: Vehicle Anomaly Detection for Highway Surveillance Videos (Mar. 2018-May 2018) Ÿ Designed a pipeline to detect anomalous vehicle from highway surveillance videos in real time Ÿ Finetuned faster and Mask R-CNN for vehicle detection Ÿ The designed algorithm was able to handle camera jittering Ÿ Our pipeline achieved first prize for CVPR Workshop competition, Nvidia AI City Challenge Track2 2018 Ÿ Summarized our work as a paper for CVPRW Project: Patient Fall-Down Detection from Hospital Surveillance Scenes (Jan. 2018-Feb. 2018) Ÿ Applied OpenPose to detect human skeletons in the scene Ÿ Designed a classifier to classify skeletons as fall-down or not, which achieved 98% accuracy on test images ## Education ### Master of Computer Vision Carnegie Mellon University ### Bachelor of Engineering (B.E.) in Electrical and Electronics Engineering Nanyang Technological University Singapore ### Exhcange Student in Informatics Kyoto University ### Summer Session Student in Electrical and Electronics Engineering UCLA ## Contact & Social - LinkedIn: https://linkedin.com/in/yushining --- Source: https://flows.cv/shining JSON Resume: https://flows.cv/shining/resume.json Last updated: 2026-03-29