Rui Cao is a cognitive scientist whose work investigates how the brain, with its biological constraints, solves complex problems in the highly dynamic and noisy environments of everyday life. Her lab combines ideas from psychology, neuroscience, and machine learning to investigate how internal temporal representations support flexible behavior. This interdisciplinary research program unfolds in two directions: (1) analyzing neural population activity using formalized cognitive models, and (2) developing biologically plausible models that capture how learning and decision-making unfold over time. Collaborating with neuroscientists and computer scientists, her lab connects abstract theories to neural data and contributes insights that inform new algorithms in artificial intelligence.

Cao earned her PhD in cognitive psychology from Indiana University under the mentorship of Professor Richard Shiffrin and Professor Robert Nosofsky, and completed postdoctoral training in computational neuroscience at Boston University with Professor Marc Howard. Her current work focuses on building computational models that incorporate scale-invariant representations of time—patterns observed in neural data—to explain how the brain maps past experience onto future expectations to guide goal-directed behavior.