Hung‐Hsuan Huang

Papers

Total Citations

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About

Hung-Hsuan Huang is a leading researcher in human-robot interaction and multimodal communication, with a focus on enabling robots to participate naturally in complex social settings like group discussions. His most-cited work, "Generation of Head Movements of a Robot Using Multimodal Features of Peer Participants in Group Discussion Conversation" (2020), addresses a critical gap in nonverbal behavior generation for conversational robots. By analyzing multimodal cues—such as gaze, speech patterns, and gestures—from human peers, Huang developed models that allow robots to produce contextually appropriate head movements, enhancing their perceived social presence and engagement. This contribution is foundational for designing robots that can seamlessly integrate into collaborative human environments, such as recruitment group discussions, where communication skills are increasingly valued. With 4 citations, this paper has influenced subsequent work on adaptive robot behavior in multiparty interactions. Huang’s broader research spans affective computing, social signal processing, and embodied conversational agents, consistently pushing the boundaries of how machines understand and replicate human social dynamics. His work is essential reading for students and researchers interested in building socially intelligent robots that can participate in, rather than merely observe, human group interactions.