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About

Julian Hough is a leading researcher in Human-Robot Interaction (HRI) and conversational AI, whose work bridges the gap between natural human communication and robotic systems. His primary research areas include grounding strategies, disfluency resolution, and multimodal communication in human-robot dialogue. Hough’s major contributions center on making robot interactions more fluid and human-like by modeling how people handle uncertainty, miscommunication, and self-repairs in conversation. His most cited work, “It’s Not What You Do, It’s How You Do It” (25 citations), demonstrates that robots must not only show legible intentions but also communicate their degree of uncertainty to users. In “Investigating Fluidity for Human-Robot Interaction” (19 citations), he developed a real-time grounding framework that explores the trade-offs between linguistic and non-linguistic actions. Hough’s research on hand motion patterns during miscommunications (10 citations) and self-repair behaviors (4 citations) reveals novel multimodal signals that improve dialogue system design. He has organized influential workshops on troubleshooting failures in HRI (6 citations) and proposed innovative virtual reality platforms for improving interaction fluidity. With over 70 total citations, Hough’s work is shaping the next generation of socially aware robots that communicate more naturally and effectively.