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About

Chee Seng Chan is a leading researcher in the intersection of computational intelligence, human motion analysis, and human-robot interaction. His work focuses on developing fuzzy qualitative approaches to address the inherent uncertainty and complexity of human motion recognition, enabling robots to understand and respond to human actions more naturally. Chan’s seminal 2009 paper, "Fuzzy Qualitative Human Motion Analysis," with 69 citations, established a computationally efficient framework that combines fuzzy logic with robot kinematics for robust motion tracking and recognition. He further advanced this field by tackling complex, multi-stage actions, as seen in his 2010 work on "Fuzzy qualitative complex actions recognition." Chan’s contributions extend to multimodal communication, notably his 2015 paper on a novel framework using robot partners for aging populations (57 citations), highlighting his commitment to socially impactful applications. His research has also explored real-time vision-based human-robot interaction and multisensory hand motion analysis. With a career spanning over a decade, Chan has published extensively, including the monograph "Human Motion Sensing and Recognition: A Fuzzy Qualitative Approach" (2017). His work is foundational for creating intelligent, adaptive robotic systems that can intuitively collaborate with humans, particularly in assistive and healthcare contexts.