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About

Yuchou Chang is a pioneering researcher at the intersection of brain-computer interfaces (BCIs), social robotics, and medical microrobotics. Their work focuses on enabling intelligent human-robot interaction by decoding human emotional and cognitive states from neurophysiological signals, particularly EEG. Chang’s key contributions include developing EEG-based emotion recognition systems that allow companion robots to dynamically adapt their behavior—a breakthrough for reducing social isolation and enhancing human-robot interaction. Their 2021 paper on this topic has garnered 12 citations, reflecting its impact on socially-aware navigation. In the realm of medical robotics, Chang has advanced magnetic resonance navigation (MRN) for micro/nano robots in blood vessels, designing path planning algorithms using A* and Q-learning to automate motion in vascular environments. Their 2018 papers on robotic path planning for magnetic resonance angiography (MRA) have each received 4 citations, contributing to non-invasive vascular interventions. Additionally, Chang has explored human-in-the-loop robotic systems for grasp-and-lift tasks, integrating human intelligence with machine autonomy. Their 2022 work on a novel convolutional neural network for emotion recognition from neurophysiological signals further underscores their commitment to healthcare innovation. With a growing citation record, Chang’s research bridges affective computing, autonomous navigation, and medical robotics, offering transformative potential for assistive technologies and clinical applications.