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About

Yixiang Jin is a leading researcher at the forefront of robotic manipulation, artificial intelligence, and human-robot interaction. His work fundamentally addresses the challenge of enabling robots to operate safely and effectively in unstructured, real-world environments. Jin’s major contributions include the development of **RobotGPT**, an innovative decision framework that leverages large language models for robotic control while critically addressing the stability and safety issues inherent in AI-generated code. This work, which has garnered over 87 citations, represents a significant step toward reliable, learning-based manipulation. He is also the architect of **ASGrasp**, the first 6-DoF grasp detection network designed to handle transparent and specular objects—a notoriously difficult problem in robotics due to the failure of standard depth sensors. This breakthrough has earned 14 citations for solving a long-standing practical challenge. Additionally, his comprehensive survey on foundation models for robot learning provides a vital roadmap for the field. Jin’s research, spanning from advanced 3D environment modeling for teleoperation to cutting-edge AI-driven manipulation, is shaping the future of universal, autonomous robots.