Libby Zhang joined the Allen Institute and the University of Washington as a Shanahan Fellow in January 2026. Broadly, she is interested in understanding how low-level sensorimotor interactions give rise to higher-level cognitive processes that support flexible and adaptive behavior across contexts and throughout life. This interest spans research areas such as multiregion and network modeling, predictive processing, and continual learning. She brings experience in hierarchical Bayesian state space modeling, and actively seeks to leverage methods that balance expressivity with interpretability.Libby earned her Ph.D. in Electrical Engineering from Stanford University. While there, she worked with Dr. Scott Linderman to develop high-dimensional time-series models and scalable inference algorithms for unsupervised behavioral analysis. These methods were applied at both subsecond timescales and at extended timescales relevant to learning, development, and aging. Prior to that, she received her B.S. and M.Eng. in Electrical Engineering from MIT, where she worked with Drs. Ann Graybiel, Michael Cima, and Helen Schwerdt to develop chronically-implantable carbon fiber microelectrode arrays for neurochemical recording.