Steven Vasquez

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About

Steven Vasquez is a rising researcher at the intersection of human-robot interaction and affective computing, with a focus on how robots can interpret and respond to human touch. His most-cited work, "Clustering Social Touch Gestures for Human-Robot Interaction" (2023, 2 citations), pioneers a data-driven approach to understanding the semantic relationships between touch gestures like stroking and patting—a critical step toward enabling robots to perceive nuanced non-verbal cues. By clustering these gestures based on their communicative intent, Vasquez provides a foundational framework for designing more intuitive and emotionally aware robotic systems. Though early in his career, his contributions address a gap in the field: while prior research cataloged touch gestures, no one had systematically mapped their relational meanings. This work has implications for assistive robotics, therapy, and social robots, where touch is a vital but underexplored channel. Vasquez’s research promises to deepen our understanding of how machines can engage in rich, tactile communication, making him a key voice in the next wave of human-robot interaction studies.