Terrence Joseph Sejnowski (born 13 August 1947) is an American computational neuroscientist and the Francis Crick Professor at the Salk Institute for Biological Studies, where he directs the Computational Neurobiology Laboratory and serves as director of the Crick-Jacobs Center for Theoretical and Computational Biology. He is also a professor of biological sciences and an adjunct professor in the departments of neurosciences, psychology, cognitive science, computer science, and engineering at the University of California, San Diego, where he co-directs the Institute for Neural Computation. Sejnowski is widely recognized for his pioneering research in neural networks and computational neuroscience, including the co-invention of the Boltzmann machine with Geoffrey Hinton and the development of the infomax algorithm for independent component analysis.
Sejnowski's work has bridged biology and machine learning, influencing fields from artificial intelligence to signal processing. He has held numerous academic positions and received many honors, including election to all four U.S. national academies. In 2025, he was elected to the American Philosophical Society and appointed a Foreign Member of the Royal Society.
Early life and education
Sejnowski was born in Cleveland, Ohio, in 1947. He earned a Bachelor of Science in physics from Case Western Reserve University in 1968. He then attended Princeton University, where he received a Master of Arts in physics under the supervision of John Archibald Wheeler and a Doctor of Philosophy in physics in 1978, advised by John Hopfield.
During his master's studies, Sejnowski analyzed the strength of gravitational waves from all known sources at the time and the sensitivity required for their detection. He concluded that all existing gravitational wave detectors were about 1000 times too insensitive, and he estimated that the necessary detectors would not be built for another 30 years. This realization led him to shift his research focus away from physics and toward biology and neuroscience.
Career and research
Sejnowski began his postdoctoral training in 1978 at Princeton University's Department of Biology, working with Alan Gelperin. From 1979 to 1981, he was a postdoctoral fellow in the Department of Neurobiology at Harvard Medical School with Stephen Kuffler. In 1982, he joined the faculty of the Department of Biophysics at Johns Hopkins University, where he rose to the rank of professor before moving to San Diego in 1988.
He held a long-standing affiliation with the California Institute of Technology, serving as Wiersma Visiting Professor of Neurobiology in 1987, Sherman Fairchild Distinguished Scholar in 1993, and part-time Visiting Professor from 1995 to 1998. In 2004, he was named the Francis Crick Professor at the Salk Institute and director of the Crick-Jacobs Center for Theoretical and Computational Biology.
Sejnowski was an investigator at the Howard Hughes Medical Institute from 1991 to 2018. His research has focused on understanding the computational resources of brains and building linking principles from brain to behavior using computational models. He has explored how dendrites integrate synaptic signals, how networks of neurons generate dynamical patterns, how sensory information is represented in the cerebral cortex, how memory representations are formed and consolidated during sleep, and how visuo-motor transformations are organized.
His laboratory has developed new methods for analyzing electrical and magnetic signals recorded from the scalp and hemodynamic signals from functional neuroimaging. He has also contributed to biophysical modeling of electrical and chemical signal processing within neurons and developed the MCell software for Monte Carlo modeling of cellular signaling.
Neural networks and the Boltzmann machine
In the early 1980s, following the work of John Hopfield, computer simulations of neural networks became widespread. Sejnowski and Geoffrey Hinton demonstrated that simple neural networks could learn tasks of some sophistication. Together, they co-invented the Boltzmann machine, a stochastic neural network that became a foundational model in deep learning. The Boltzmann machine's ability to learn complex probability distributions influenced later developments in machine learning and generative AI.
Sejnowski also pioneered the application of learning algorithms to difficult problems in speech and vision. He developed NETtalk, a neural network that learned to read English text aloud. With his postdoctoral fellow Tony Bell, he developed the infomax algorithm for independent component analysis (ICA), which has been widely adopted in machine learning, signal processing, and data mining.
In 1989, Sejnowski founded the journal Neural Computation, published by MIT Press, which became a leading journal in neural networks and computational neuroscience. He also serves as president of the Neural Information Processing Systems Foundation, which oversees the annual NeurIPS conference, a major interdisciplinary meeting that brings together researchers from biology, physics, mathematics, and engineering.
Teaching and public engagement
Sejnowski co-created and taught the online course "Learning How to Learn: Powerful mental tools to help you master tough subjects" with Barbara Oakley. The course, available on Coursera, has become the world's most popular online course. It teaches evidence-based learning techniques, including spaced repetition and interleaving, and has reached millions of learners worldwide.
His teaching and public engagement efforts have helped popularize neuroscience and learning science, making complex topics accessible to a broad audience.
Honors and awards
Sejnowski has received numerous honors throughout his career. In 1984, he received a Presidential Young Investigator Award from the National Science Foundation. He received the Wright Prize from Harvey Mudd College in 1996 for excellence in interdisciplinary research and the Hebb Prize from the International Neural Network Society in 1999 for contributions to learning algorithms.
He became a Fellow of the Institute of Electrical and Electronics Engineers in 2000 and received their Neural Network Pioneer Award in 2002. In 2003, he was elected to the Johns Hopkins Society of Scholars. He is a Senior Fellow of the Design Futures Council.
Sejnowski was elected to the National Academy of Medicine in 2008, the National Academy of Sciences in 2010, the National Academy of Engineering in 2011, and the National Academy of Inventors in 2017. This places him in a group of only three living people elected to all four U.S. national academies. He was elected to the American Academy of Arts and Sciences in 2013 and became a Fellow of the American Physical Society in 2014.
He received the Swartz Prize for Theoretical and Computational Neuroscience from the Society for Neuroscience in 2015, an honorary doctorate from the University of Zurich in 2017, and the Gruber Neuroscience Prize in 2022. In 2024, he was awarded The Brain Prize for pioneering work in theoretical neuroscience, shared with Larry Abbott and Haim Sompolinsky, and received an honorary Doctor of Science from Princeton University. In 2025, he was appointed a Foreign Member of the Royal Society and elected to the American Philosophical Society.
Legacy and influence
Sejnowski's contributions have had a lasting impact on both neuroscience and artificial intelligence. His work on neural networks laid groundwork for modern deep learning, and his insights into brain function have informed computational models used in machine learning. His research on independent component analysis has applications in signal processing and data mining.
As a mentor and educator, he has influenced a generation of researchers in computational neuroscience. His interdisciplinary approach, combining biology, physics, and computer science, has helped shape the field of computational neuroscience. His ongoing work at the Salk Institute continues to explore the computational resources of brains, aiming to build linking principles from brain to behavior.