Papers
1
Total Citations
3
H-Index
1
About
Ho Shu Chan is a researcher at the forefront of human-robot interaction, with a focused expertise in developing dialogue systems for humanoid robots in healthcare settings. Their most cited work, "A Humanoid Robot Dialogue System Architecture Targeting Patient Interview Tasks" (2024), addresses a critical challenge: leveraging the human-like appearance of robots to conduct routine patient interviews while managing the heightened expectations that anthropomorphism creates. This research bridges robotics, natural language processing, and clinical practice, proposing an architecture that balances verbal and behavioral cues essential for effective medical communication. Though early in its publication journey with 3 citations, this work signals significant potential for transforming how automated systems interact with patients, particularly in triage and data collection. Chan's contributions lie at the intersection of engineering and empathy, exploring how robots can adopt the nuanced social behaviors required for sensitive healthcare interactions. Their work is particularly notable for tackling the "uncanny valley" problem in medical contexts, where trust and rapport are paramount. As healthcare increasingly turns to automation, Chan's research offers a foundational framework for designing robots that are both functionally effective and socially acceptable—a critical step toward integrating humanoid assistants into clinical workflows.
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Top Papers
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