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About

Changchun Yang is a leading researcher at the intersection of autonomous systems, robotics, and data privacy, with a primary focus on trajectory prediction and simultaneous localization and mapping (SLAM). His work addresses critical challenges in enabling safe and intelligent navigation for self-driving vehicles, delivery robots, and social robots. Yang’s most significant contributions include pioneering a federated pedestrian trajectory prediction model that safeguards data privacy while maintaining high accuracy—a crucial advancement for real-world deployment where sensitive trajectory data is scattered across different scenes. He has also developed a multi-granularity scenarios understanding network that deciphers complex scene layouts to better predict uncertain future motions. In the domain of robotics, Yang advanced SLAM technology by fusing LiDAR and IMU data, dramatically improving localization accuracy for wheeled robots operating in noisy manufacturing environments. His most cited works have garnered 17 citations each, reflecting their growing influence in the autonomous systems community. Through these innovations, Yang is helping to build the foundational technologies for a future where robots and autonomous vehicles can navigate safely, efficiently, and privately.