Terrence Sejnowski

Terrence J. Sejnowski is a computational neuroscientist known for foundational work in neuroscience and artificial intelligence. Sejnowski serves as a professor, head of the Computational Neurobiology Laboratory, and holds the Francis Crick Chair at the Salk Institute for Biological Studies. He is also a Distinguished Professor of Neurobiology at UC San Diego. His research focuses on understanding the principles that link brain function to behavior. Sejnowski is a member of the National Academy of Sciences, National Academy of Engineering, National Academy of Medicine, and National Academy of Inventors, one of only three living scientists elected to all four national academies.

Sejnowski co-invented the Boltzmann machine with Geoffrey Hinton, an algorithm that addressed learning in multilayered neural networks and remains influential in artificial neural network research. He pioneered NETtalk, a computer program that learned to convert written text into speech, contributing to the development of modern artificial intelligence and natural language processing tools. Sejnowski also developed Independent Component Analysis, a machine learning algorithm for blind source separation of mixed signals. He is president of the Neural Information Processing Systems Foundation, which organizes a major annual conference in machine learning and neural computation, and is the founding editor-in-chief of "Neural Computation," published by MIT Press.

Sejnowski has published more than 300 scientific papers and 12 books, including "The Computational Brain" with Patricia Churchland. His work includes "Liars, Lovers, and Heroes," "The Deep Learning Revolution," and "ChatGPT and the Future of AI." He has contributed to national science policy as an advisor to the White House BRAIN Initiative and is active in science communication, including media appearances and the online course "Learning How to Learn" on Coursera.

Sejnowski has received major honors in neuroscience and artificial intelligence, including the Brain Prize for contributions to theoretical and computational neuroscience, the Gruber Neuroscience Prize for pioneering work in the field, and the NIH Director's Pioneer Award for research on neural circuit dynamics of working memory. His interdisciplinary approach has influenced both neuroscience and artificial intelligence, advancing understanding of brain function and machine learning.