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About

Laurence C. Jayet Bray pioneers the interdisciplinary field of neurorobotics, where cognitive neuroscience meets artificial intelligence to create socially aware robots. His research focuses on three key areas: goal-directed navigation in neuromorphic systems, human-robot interaction (HRI) mediated by trust and intent recognition, and reward-based learning through emotional speech processing. Bray’s most influential work, "Goal-related navigation of a neuromorphic virtual robot" and "Real-time human–robot interaction underlying neurorobotic trust and intent recognition" (each with 9 citations), demonstrates how biologically inspired neural architectures can enable robots to navigate environments and interpret human social cues in real time. Notably, his 2011 study "Modeling oxytocin induced neurorobotic trust" (5 citations) was among the first to computationally model the neuropeptide oxytocin’s role in fostering trust during HRI, drawing on human pharmacological fMRI studies. This groundbreaking approach bridges social neuroscience and robotics, offering a framework for machines that can build trust through social risk assessment. Bray’s work on reward-based learning via emotional speech further advances adaptive HRI, positioning him as a key contributor to the development of empathetic, neurorobotic systems.