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About

Wei Liang Chan is a robotics researcher whose work sits at the intersection of human-robot interaction, control theory, and artificial intelligence. He is best known for pioneering contributions to **physical human-robot collaboration**, with a particular focus on developing intelligent shared control frameworks that allow robots to dynamically adapt their roles alongside human partners. Chan's most influential contribution, "Continuous Role Adaptation for Human–Robot Shared Control" (2015), has garnered 186 citations and introduced a game-theoretic approach enabling robots to fluidly adjust their level of autonomy in response to human intent—whether to lead or follow. This foundational work was complemented by a 2016 framework integrating policy iteration to compute Nash equilibrium solutions in human-robot systems, which has attracted 129 citations and remains a key reference in cooperative robotics literature. Across multiple publications, Chan consistently applies game theory and adaptive optimal control to solve the nuanced challenge of role-sharing between humans and machines, advancing both theoretical understanding and practical implementation. His research also extends to industrial and service robotics, exploring intuitive teleoperation interfaces that move beyond rigid, pre-programmed trajectories. Collectively, his body of work has shaped modern thinking on how robots can become genuinely responsive and collaborative partners in shared tasks.