Sangmook Lee

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About

Sangmook Lee is a researcher working at the intersection of neuroscience, robotics, and artificial intelligence, with a particular focus on bridging biological and computational neural systems. His work explores how living neuronal networks — specifically cultured murine cortical neurons — can be interfaced with robotic platforms to study learning and adaptive behavior in closed-loop environments. Lee's most notable contributions include pioneering systems that allow biological neuronal cultures to directly control robotic hardware, such as a robot arm, enabling real-time interaction between living neural tissue and physical environments. His 2017 paper on robot-embodied neuronal networks advanced the reductionist study of synaptic signaling by situating neural cultures within interactive mechanical systems, while his comparative work demonstrated that biological and simulated neuronal networks exhibit remarkably similar performance on visual tracking tasks. This finding has significant implications for validating computational models of neural behavior. Collectively accumulating 11 citations, Lee's research contributes foundational tools and frameworks for the emerging field of neuromorphic robotics and offers valuable insights into the fundamental mechanisms of neural learning and plasticity.