Louis Tao is a Professor of Life Sciences at Peking University and a computational neuroscientist who has long worked at the intersection of dynamical systems, stochastic spiking-network modeling, and model reduction. His research aims to transform biologically detailed circuit models into tractable mathematical objects that preserve key dynamical mechanisms. He is best known for developing mechanism-driven, mathematically explicit frameworks that bridge three levels in a single program: spiking-circuit biophysics, low-dimensional dynamical structure, and scalable algorithms that run efficiently on modern hardware. His current work spans neuronal population dynamics, brain-inspired computing, and the neural circuitry of behavior in both model organisms.

During the fellowship, Louis hopes to write a short conceptual history of cognitive science organized around the problem of the homunculus: the tendency to explain cognitive capacities by quietly placing inside the system something that already sees, remembers, judges, or decides. The goal is not to reject models, metaphors, or AI, but to ask when they genuinely clarify cognition, and when they simply move the hard part into unexamined mechanisms, fitted parameters, or technical language. In the age of AI, we need a sharper account of what it means for a model to explain, rather than merely reproduce, intelligent behavior.