Terry Sejnowski, Ph.D.
Francis Crick Professor and the Director of the Crick-Jacobs Center for Theoretical and Computational Biology, Salk Institute
Scientific Advisory Board Member, Flatiron Institute

From 1978–1979 Sejnowski was a postdoctoral fellow in the Department of Biology at Princeton University with Alan Gelperin and from 1979–1981 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 the Johns Hopkins University, where he achieved the rank of Professor before moving to San Diego, California in 1988. He was an Investigator at the Howard Hughes Medical Institute from 1991 to 2018.
He has had a long-standing affiliation with the California Institute of Technology, as a Wiersma Visiting Professor of Neurobiology in 1987, as a Sherman Fairchild Distinguished Scholar in 1993 and as a part-time Visiting Professor 1995–1998. In 2004, he was named the Francis Crick Professor at the Salk Institute and the director of the Crick-Jacobs Center for Theoretical and Computational Biology.
His research in neural networks and computational neuroscience has been pioneering. In the early 1980s, particularly following work by John Hopfield, computer simulations of neural networks became widespread. Early applications, particularly by Sejnowski and Geoffrey Hinton, demonstrated that simple neural networks could be made to learn tasks of at least some sophistication. In 1989, Sejnowski founded Neural Computation, published by the MIT Press, the leading journal in neural networks and computational neuroscience. He is also the President of the Neural Information Processing Systems Foundation, a non-profit organization that oversees the annual NeurIPS Conference. This interdisciplinary meeting brings together researchers from many disciplines, including biology, physics, mathematics, and engineering.
The long-range goal of Sejnowski’s research is to understand the computational resources of brains and to build linking principles from brain to behavior using computational models. This goal is being pursued with a combination of theoretical and experimental approaches at several levels of investigation ranging from the biophysical level to the systems level. Hippocampal and cortical slice preparations are being used to explore the properties of single neurons and synapses, including the precision of spike firing and the influence of neuromodulators. Biophysical models of electrical and chemical signal processing within neurons are used as an adjunct to physiological experiments.
The central issues being addressed are how dendrites integrate synaptic signals in neurons, how networks of neurons generate dynamical patterns of activity, how sensory information is represented in the cerebral cortex, how memory representations are formed and consolidated during sleep, and how visuo-motor transformations are adaptively organized. His laboratory has developed new methods for analyzing the sources for electrical and magnetic signals recorded from the scalp and hemodynamic signals from functional neuroimaging by blind separation using ICA. The EEGLAB public software which was as of 2012 the most popular software for processing EEG data was originally developed in his laboratory.