Daniel Schulman

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About

Daniel Schulman’s research lies at the intersection of human-computer interaction, relational agents, and affective computing, with a focus on designing socially intelligent systems that foster genuine, lasting engagement. His most influential work, “Relational Agents Improve Engagement and Learning in Science Museum Visitors” (2011, 74 citations), demonstrates how virtual agents employing human relationship-building behaviors can significantly enhance visitor learning and interaction in public spaces. This study established foundational design principles for deploying social agents in real-world environments, showing that strategic displays of affect and relational cues can transform passive observation into active, meaningful participation. Schulman’s earlier paper, “Public Displays of Affect” (2008, 20 citations), further codified these principles, exploring how agents can use emotional expression to build rapport and trust with users in public settings. His contributions have been pivotal in advancing the field of relational agents, bridging the gap between theoretical affective computing and practical, deployable systems. Schulman’s work continues to influence the design of educational technologies, museum guides, and public-facing interactive systems, making him a key figure in creating technology that connects with people on a human level.