Jonathan Juett

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About

Jonathan Juett is a robotics and cognitive systems researcher whose work sits at the intersection of developmental psychology and machine learning, with a particular focus on how autonomous agents can learn to navigate and interact with peripersonal space — the immediately reachable environment surrounding an agent's body. Drawing inspiration from how human infants develop sensorimotor capabilities in the first months of life, Juett has pioneered computational models that allow robotic systems to acquire reaching and grasping skills with minimal prior knowledge of geometry, kinematics, or dynamics. His most influential work, "Learning and Acting in Peripersonal Space" (2019, 11 citations), synthesizes empirical infant development research with robotic learning architectures, offering a unified framework for understanding how both biological and artificial agents build internal models of their surroundings. Complementary papers from 2016 and 2018 demonstrate progressive milestones in this research agenda — from constructing graph-based spatial representations to extending those representations to support grasping behavior. With a cumulative citation count of 26 across three closely related works, Juett has established a coherent and growing research identity. His contributions are particularly valuable for students interested in developmental robotics, embodied cognition, and biologically inspired machine learning.