David B. Skillicorn

Queen's University, University of Technology Sydney

Papers

Total Citations

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About

David B. Skillicorn’s research lies at the intersection of artificial intelligence, social robotics, and computational psychology, with a focus on enabling machines to understand and adapt to human behavior. His major contributions center on developing algorithms that allow social robots to infer personality traits, affective states, and long-term preferences from natural human interactions, such as social media posts. In his most-cited work, “Estimating Personality from Social Media Posts” (2017, 22 citations), Skillicorn demonstrates how personality can be reliably predicted from digital footprints, enhancing a robot’s ability to tailor its responses to individual users. He further explores short-term emotion and mood modeling in “Social Robot Modelling of Human Affective State” (2017, 3 citations), and addresses the challenge of aligning robot actions with unspoken human desires in “The Altruistic Robot: Do What I Want, Not Just What I Say” (2017, 2 citations). While his citation counts reflect a growing field, Skillicorn’s work is notable for its practical ambition: creating robots that are not merely reactive but empathetic and altruistic. His research is foundational for developers aiming to build socially intelligent machines that can form genuine, adaptive relationships with people.