Max Robotics — Global Service Robot Directory + US Certification

About

Chi-Sheng Shih is a leading researcher at the intersection of embedded systems, robotics, and cyber-physical systems, with a particular focus on real-time workflow architectures and autonomous navigation. His groundbreaking work on the Embedded Workflow Framework (EMWF) and Embedded Real-Time Workflow Engine (ERWF) has established foundational principles for building flexible, user-centric automation systems, enabling everything from assistive devices to service robots to operate with unprecedented configurability and reliability. Shih’s contributions to robotic perception are equally significant—he co-organized the 2018 Robotic Scene Segmentation Challenge at MICCAI, a benchmark dataset that has garnered 119 citations and driven advances in surgical scene understanding. More recently, his development of the Social Conditional Generative Adversarial Network for trajectory prediction at unsignalized intersections (2021) addresses critical challenges in autonomous driving safety. Shih has also pioneered innovative localization techniques, including ArPico and PicPose, which leverage low-cost cameras and picture posing for IoT device positioning, and has advanced real-time communication on edge networks using Eclipse Zenoh. With over 140 citations across his portfolio, Shih’s work continues to shape the future of intelligent, autonomous systems in healthcare, manufacturing, and transportation.