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About

Kristsana Seepanomwan is a pioneering researcher at the intersection of developmental robotics, cognitive neuroscience, and artificial intelligence. Their work fundamentally explores how robots can autonomously acquire complex cognitive and motor skills, drawing inspiration from human development. A major contribution is the use of intrinsic motivations—an agent’s internal drive to explore and learn—to boost goal achievement, as demonstrated in their 2017 study on a humanoid robot (25 citations). Seepanomwan is also renowned for modeling mental rotation, a classic cognitive psychology paradigm, in robotic systems. Their 2015 paper (24 citations) and 2013 paper (18 citations) introduced a neurorobotic architecture that explains how embodiment and decision-making affect mental rotation, bridging the gap between human cognition and machine learning. More recently, their 2020 work (5 citations) proposed a developmental-robotics model to explain the sudden emergence of tool use in human infants, offering two competing hypotheses grounded in intrinsic motivations and planning. By integrating computational models with real robotic platforms, Seepanomwan provides profound insights into how intelligent agents—both biological and artificial—learn, plan, and interact with their environment, making their research essential for students and researchers in cognitive robotics and developmental AI.