Regular biography
Sebastian Seung is the Anthony B. Evnin ’62 Professor in Neuroscience and professor of computer science at Princeton University. He is affiliated with the Princeton Neuroscience Institute and has conducted influential research in computer science and neuroscience. Seung has pioneered work in connectomics, developing machine learning and social computing technologies for reconstructing neural circuits from high-resolution brain images. He joined Princeton in 2014 after teaching at MIT and completing his doctoral work at Harvard. His research has been recognized with awards such as the Wiley Prize in Biomedical Sciences and the 2026 Pradel Award from the National Academy of Sciences. He is a member of the National Academy of Sciences and an external member of the Max Planck Society.
Scholar-generated biography
H Sebastian Seung is a professor at Princeton Neuroscience Institute and Computer Science Department, specializing in computational neuroscience and connectomics. His research focuses on understanding the brain's structure and function through computational models and advanced imaging techniques. He has developed algorithms for non-negative matrix factorization, which are used in machine learning and image processing. His work includes connectomic reconstructions of brain regions such as the inner plexiform layer and neocortex, contributing to the study of how neural wiring shapes cognition. Seung's research also explores natural image processing, neuronal population coding, and silicon circuits inspired by the cortex. His publications highlight the intersection of neuroscience, machine learning, and systems biology in unraveling the complexities of the brain.