Jiaying Chen

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About

Jiaying Chen is a leading researcher in autonomous navigation and robotics, specializing in LiDAR-based perception, simultaneous localization and mapping (SLAM), and deep reinforcement learning for mobile platforms. Her work addresses critical challenges in enabling robots to operate reliably in large-scale, unstructured environments. Chen’s major contributions include the development of a novel LiDAR-based end-to-end active SLAM system that leverages deep reinforcement learning, dramatically improving autonomous exploration efficiency in expansive settings where traditional algorithms suffer from computational overhead. She also introduced a versatile LiDAR-inertial odometry framework incorporating SE(2) constraints specifically designed for ground vehicles, extending the capabilities of foundational systems like LOAM by fusing onboard sensor data for enhanced localization accuracy. Her research has garnered significant attention, with her most-cited papers accumulating over 27 citations in just two years, reflecting their immediate impact on the field. Chen’s work is notable for its practical focus on real-world deployment, offering scalable solutions that push the boundaries of autonomous exploration and navigation in complex environments.