Max Robotics — Global Service Robot Directory + US Certification

About

Zheyuan Lin is a researcher at the forefront of human-robot interaction (HRI), focusing on enabling robots to perceive, understand, and respond to human social cues. His work integrates computer vision, multi-modal sensing, and deep learning to make service robots safer and more intuitive. Lin’s major contributions include developing a depth-aware gaze-following framework that leverages auxiliary networks to predict where a person is looking without requiring extra training data—a crucial skill for collaborative robotics. He also created the TGRMPT dataset and tracker, specifically designed for the challenging environment of tour-guide robots, enabling robust multi-person tracking in crowded spaces. To improve social fluency, Lin pioneered addressee detection systems that fuse facial and audio features, allowing robots to determine if they are being spoken to in mixed human-human and robot settings. His work on multi-scale graph convolutional networks (MSMB-GCN) advances 3D human pose estimation from 2D data, further enhancing a robot’s ability to interpret body language. With over 40 citations to his most-cited works, Lin’s research is laying the groundwork for the next generation of socially aware, autonomous service robots.