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About

Pei-Hsuan Tsai is a researcher whose work spans computer vision, human-robot interaction, and intelligent systems for safety-critical applications. Her primary research areas include dynamic hand gesture recognition, robot teleoperation error mitigation, search and rescue optimization, and medication error prevention. Tsai's most impactful contribution is an efficient graph convolution network for skeleton-based dynamic hand gesture recognition (2023, 23 citations), which addresses the over-parameterization problem in state-of-the-art methods, making real-time human-computer interaction more practical. She has also developed a speed-up approach for search and rescue operations (2018, 6 citations) that minimizes response time in challenging environments, and proposed target prediction techniques to reduce human errors in robot teleoperation systems (2017, 5 citations). Her work on point-of-care support for error-free medication processes (2007, 5 citations) demonstrates her commitment to healthcare safety, while her self-evacuation approach for robots in fire disasters (2023, 4 citations) tackles the vulnerability of costly sensors in hazardous environments. Tsai's research consistently focuses on making autonomous systems more reliable, efficient, and safe across diverse application domains.