Ian Steenstra

Papers

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About

Ian Steenstra’s research lies at the intersection of human-robot interaction, conversational AI, and affective computing, with a focus on making multiparty dialogues more natural and empathetic. In his highly cited 2023 work, *Improving Multiparty Interactions with a Robot Using Large Language Models* (23 citations), Steenstra tackled the challenge of speaker diarization in co-located group settings—enabling robots to identify who said what, moderate participation, and deliver personalized responses. This foundational contribution addresses a critical bottleneck in meeting facilitation robots and collaborative AI systems. Building on this, his 2024 paper, *Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents* (11 citations), introduced a novel extension of Clark’s grounding theory. Steenstra proposed that for truly human-like interaction, conversational agents must not only establish mutual understanding but also recognize and respond to the speaker’s affective state—what he terms “empathic grounding.” By integrating multimodal cues with large language models, his work pushes beyond simple task completion toward emotionally aware dialogue systems. Steenstra’s research is shaping the next generation of socially intelligent robots capable of fluid, empathetic group interaction.