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About

David Traum is a leading researcher in human-robot interaction, spoken dialogue systems, and computational linguistics, whose work sits at the fascinating intersection of artificial intelligence, language technology, and social robotics. Best known for his foundational contributions to dialogue management and natural language processing for interactive agents, Traum has helped shape how machines understand and respond to human communication. His highly cited 2021 paper on spoken language interaction with robots (106 citations) established critical research directions for the field, while his innovative work on teaching sign language to deaf infants using robots and virtual humans (55 citations) demonstrates his commitment to socially impactful applications. Traum's research into trust, rapport, and social dialogue in human-robot teams has illuminated how conversational errors and relationship-building strategies shape user behavior, generating significant scholarly interest. His technical contributions extend to augmenting Abstract Meaning Representation for situated robot dialogue and exploring multimodal dialogue management for vulnerable populations including infants. Additionally, his early work on computational deception broadens his intellectual range into adversarial agent behavior. Across more than a decade of published research, Traum has consistently advanced our understanding of how intelligent systems can engage humans more naturally, meaningfully, and ethically.