Alan Huang

Papers

Total Citations

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About

Alan Huang’s research lies at the intersection of human-robot interaction, cognitive science, and attention guidance, with a focus on how robots can intuitively direct human focus. His most-cited work, “Directing human attention with pointing” (2014, 7 citations), explores the nuanced mechanics of robot pointing behaviors—a fundamental yet understudied aspect of non-verbal communication in collaborative settings. Through carefully designed experiments, Huang demonstrated how subtle variations in a robot’s pointing gestures influence human attention allocation, laying groundwork for more natural human-robot teamwork. While his citation count is modest, the work’s impact is significant in specialized fields like assistive robotics and autonomous systems, where effective attention direction is critical for safety and efficiency. Huang’s contributions bridge behavioral psychology and robotics, offering empirical insights that inform the design of socially aware machines. His research is particularly valuable for students and engineers developing robots for shared environments—from manufacturing floors to healthcare settings—where seamless human-robot coordination depends on clear, intuitive cues. By quantifying how people respond to robotic gestures, Huang helps advance the frontier of machines that truly understand human social signals.