Tai Sing Lee

Tai Sing Lee is a Professor in the School of Computer Science and a core faculty member of the Neuroscience Institute at Carnegie Mellon University. His research focuses on computational neuroscience, systems neuroscience, and the intersection of machine learning with biological neural systems. Key areas include neural circuit characterization, learning mechanisms, and perceptual inference.

His work combines theoretical modeling with empirical data from neurophysiological experiments, particularly in visual cortex regions like V1, V2, and V4. Notable contributions include studies on neural encoding of natural scenes, recurrent cortical circuit dynamics, and the application of self-supervised learning principles in artificial vision systems.

Lee's research also explores how neural systems integrate contextual information and adapt to environmental statistics, with implications for both biological understanding and AI development. He has pioneered methods for analyzing large-scale calcium imaging datasets to uncover organizational principles in visual cortex.