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About

Wei-Han Liu is a pioneering researcher in the field of human-robot interaction and auditory perception for autonomous systems. His work focuses on integrating speech and vision to create more natural, robust communication interfaces between humans and mobile robots. Liu’s major contributions include the development of a real-time speaker attention system that combines microphone array processing with face tracking, enabling robots to focus on a speaking human in dynamic environments. He also advanced robot localization by introducing the Gaussian mixture-sound field landmark model (GM-SFLM), a novel approach that uses statistical patterns of sound fields—rather than geometric source locations—to determine a robot’s position and orientation, even in noisy, complex settings. His most cited work, the 2006 paper on the speaker attention system, has garnered 16 citations, while his sound-field-based localization methods have collectively received over a dozen citations, demonstrating their influence in the robotics community. Liu’s innovative use of auditory landmarks for pose detection represents a significant step toward making robots more perceptually aware in real-world environments.