Terry Sejnowski
TL;DR Terrence J. Sejnowski is a pioneering neuroscientist and computational biologist whose research has shaped our understanding of learning, memory, and the biological foundations of artificial intelligence.
Terry Sejnowski by Sora
Terry Sejnowski is an American neuroscientist, computational biologist, and one of the key figures in connecting neuroscience and artificial intelligence. His interdisciplinary work has influenced how scientists and engineers think about neural computation, learning, and the structure of intelligent systems. As a professor at the Salk Institute for Biological Studies and the University of California, San Diego (UCSD), Sejnowski has spent decades exploring how the brain processes information, work that has guided both brain science and AI research.
Born in Cleveland, Ohio, in 1947, Sejnowski earned his Ph.D. in physics from Princeton University. Early in his career, he became known for combining mathematics, biology, and computer science to model neural networks. His most famous contribution came through the development of the Boltzmann machine, a type of stochastic neural network created in collaboration with Geoffrey Hinton. This model became a cornerstone for modern deep learning and probabilistic AI.
Beyond neural network theory, Sejnowski’s work has delved deeply into how the brain encodes and transmits information, contributing to breakthroughs in understanding neural plasticity and synaptic learning. He also served as President of the Neural Information Processing Systems (NeurIPS) Foundation, helping shape one of the world’s most influential AI research communities. His research continues to bridge the gap between the human brain and intelligent machines, showing how insights from neuroscience can inspire new forms of artificial cognition.
Co-creator of the Boltzmann Machine, one of the foundational architectures in modern neural network research
Professor at the Salk Institute and UC San Diego, advancing neuroscience and computational biology.
Pioneer in theoretical neuroscience, modeling how neurons encode, store, and process information
President of the Neural Information Processing Systems (NeurIPS) Foundation, guiding global AI research collaboration.
Member of the National Academy of Sciences, recognized for contributions to both AI and neuroscience.
Author of “The Deep Learning Revolution,” chronicling the rise of neural networks and their connection to brain science
Leader in bridging biological and artificial intelligence, shaping how we understand cognition and machine learning today
