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Terrence Sejnowski

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Terrence Joseph Sejnowski is an Investigator with the Howard Hughes Medical Institute and is the Francis Crick Professor at The Salk Institute for Biological Studies where he directs the Computational Neurobiology Laboratory. He is also Professor of Biological Sciences and Adjunct Professor in the Departments of Neurosciences, Psychology, Cognitive Science, and Computer Science and Engineering at the University of California, San Diego, where he is Director of the Institute for Neural Computation. In 2004 he was named the Francis Crick Professor and the Director of the Crick-Jacobs Center for Theoretical and Computational Biology at the Salk Institute. His research in neural networks and computational neuroscience has been pioneering.

EducationEdit

Sejnowski received B.S. in physics from the Case Western Reserve University, M.A. in physics from Princeton University, and a Ph.D. in physics from Princeton University in 1978. From 1978-1979 Sejnowski was a postdoctoral fellow in the Department of Biology at Princeton University and from 1979-1982 he was a postdoctoral fellow in the Department of Neurobiology at Harvard Medical School. 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 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.

AwardsEdit

Sejnowski received a Presidential Young Investigator Award in 1984 from the National Science Foundation. He received the Wright Prize from the Harvey Mudd College for excellence in interdisciplinary research in 1996 and the Hebb Prize for his contributions to learning algorithms by the International Neural Network Society in 1999. 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.

ProfessionalEdit

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 NIPS Conference. This interdisciplinary meeting brings together researchers from many disciplines, including biology, physics, mathematics, and engineering. He co-invented the Boltzmann machine with Geoffrey Hinton and pioneered the application of learning algorithms to difficult problems in speech (NETtalk) and vision.

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.

New techniques have been developed for modeling cell signaling using Monte Carlo methods (MCell). 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 independent component analysis (ICA).

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