Kailai Sun

Singapore-MIT Alliance for Research and Technology, Tsinghua University

Papers

Total Citations

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About

Kailai Sun is a researcher whose work spans the intersection of robotics, artificial intelligence, and traditional medicine, with a focus on safety-critical systems and human-robot interaction. His key research areas include pedestrian tracking, control barrier functions for nonlinear systems, and the integration of robotics with traditional Chinese medicine (TCM). Sun’s major contributions are highlighted by his development of a multi-source data fusion network for pedestrian head tracking, which addresses a critical gap in autonomous navigation and surveillance, as evidenced by his most-cited paper (8 citations). He also pioneered a visual feedback system for a TCM massage robot, a novel application that aims to alleviate the shortage of skilled acupuncturists by automating physiotherapy techniques. Additionally, Sun proposed a learning-based method for computing control barrier functions to ensure safety in nonlinear systems, a vital advancement for robotic and automotive safety controllers (3 citations). His work not only advances technical fields like control theory and computer vision but also bridges cultural heritage with modern engineering, demonstrating a unique interdisciplinary impact. Sun’s achievements underscore his role in enhancing both technological safety and healthcare accessibility.