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About

Yeong‐Dae Kim is a pioneering researcher at the intersection of human-robot interaction, cognitive neuroscience, and manufacturing systems. His work primarily explores how humans perceive and trust AI-controlled systems, with a particular focus on electromyography (EMG)-based robot control and the neural correlates of user satisfaction. Kim’s major contributions include developing frameworks for understanding trust in human-AI interaction—a critical area as autonomous systems become ubiquitous—and demonstrating that electroencephalography (EEG) can objectively reflect user satisfaction during robot control. His 2022 paper on trust models, with 77 citations, has become a foundational reference for researchers studying how people evaluate AI-infused systems, from robots to smart vehicles. Additionally, his 2021 study on brain activity during delayed input in EMG-controlled robots (7 citations) provides key insights into designing more intuitive control interfaces. Earlier in his career, Kim contributed to flexible manufacturing systems, developing heuristic algorithms for tool loading and scheduling. His interdisciplinary approach—bridging engineering, psychology, and neuroscience—has positioned him as a leading voice in creating AI systems that are both efficient and trustworthy, making his work essential reading for students and researchers in human-robot interaction and cognitive engineering.