Rosalyn Moran

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About

Rosalyn Moran is a leading computational neuroscientist whose work bridges the gap between brain function and artificial intelligence. Her primary research focuses on understanding how the brain builds and updates internal models of the world—a process central to perception, learning, and decision-making. In her highly cited 2021 paper, "World model learning and inference" (81 citations), Moran explores how the brain’s hierarchical structure supports sophisticated cognition and control, offering insights that inform both neuroscience and the development of general-purpose AI. Her contributions have significantly advanced the field of active inference, a framework that unifies action, perception, and learning under a single mathematical principle. With a citation count reflecting her growing influence, Moran’s work is recognized for its interdisciplinary reach, impacting fields from psychiatry to robotics. She is also known for her collaborative efforts in translating theoretical models into practical applications, making her a pivotal figure in the quest to understand human intelligence and replicate its distinctive features in artificial systems.