STEPHEN GROSSBERG
Wang Professor of Cognitive and Neural
Systems
Professor of Mathematics, Psychology, and
Biomedical Engineering
Chairman, Department of Cognitive and
Neural Systems
Director, Center for Adaptive Systems
(617) 353-7857
(617) 353-7755
www.cns.bu.edu/Profiles/Grossberg
HIGH SCHOOL:
First in
Class of 1957
COLLEGE:
First in
Class of 1961
A.P. Sloan
National Scholar
Phi Beta
Kappa Prize
NSF
Undergraduate Research Fellow
GRADUATE WORK:
NSF Graduate
Fellowship
Woodrow
Wilson Graduate Fellowship
POST-GRADUATE ACTIVITIES:
1. Assistant Professor of Applied
Mathematics, M.I.T., 1967-1969.
2. Senior Visiting Fellow of the Science
Research Council of
3. Norbert Wiener Medal for Cybernetics,
1969.
4. A.P. Sloan Research Fellow, 1969-1971.
5. Associate Professor of Applied
Mathematics, M.I.T., 1969-1975.
6. Professor of Mathematics, Psychology, and
Biomedical Engineering,
7. Invited lectures in
8. Editor of the journals Adaptive
Behavior; Applied Intelligence; Behavioral and Brain Sciences
(Associate Editor for Computational
Neuroscience); Behavioural Processes; Brains, Minds, and Media; Cognition and Brain Theory; Cognitive
Brain Research; Cognitive
Neurodynamics; Cognitive Processing; Cognitive Science; Current Opinions in Cognitive Neurodynamics; IEEE
Expert; IEEE Transactions on Neural Networks; Information
Sciences; International Journal of Cognitive Science; International Journal of Humanoid Robotics; International Journal of Hybrid Intelligent
Systems; International Journal of Neural Systems; International Journal of Uncertainty, Fuzziness, and Knowledge-Based
Systems; Journal of Cognitive Neuroscience; Journal of Experimental Neuroscience, Journal
of Mathematical Psychology; Journal of Theoretical Neurobiology; Mathematical
Biosciences; Mind and Society;
Neural Computation; Nonlinear Analysis.
9. Editorial board member of the book series
Advanced Information and Knowledge Processing, Springer-Verlag; Mathematical
Modeling: Theory and Applications, Kluwer.
10.
Founding
editor-in-chief of the journal Neural Networks.
11.
Founder
and First President of the International Neural Network Society and member of
founding governing board of the Society.
12.
Founder
and Director, Center for Adaptive Systems,
13.
Principal
Investigator,
14.
Wang
Professor of Cognitive and Neural Systems,
15.
Founder
and Chairman, Department of Cognitive and Neural Systems, Boston University,
1991-2007.
16.
IEEE
Neural Networks Pioneer Award, 1991.
17.
18.
INNS
Leadership Award, 1992.
19.
Fellow,
American Psychological Association (APA), 1994.
20.
Principal
Investigator, Center for Automated Vision and Sensing Systems (Congressional
21.
Fellow,
Society of Experimental Psychologists (SEP), 1996.
22.
Information
Sciences Award, Association for Intelligent Machinery, 2000.
23.
Principal
Investigator, Center for Intelligent Biomimetic Image Processing and
Classification (Congressional
24.
Charles
River Laboratories prize, Society for Behavioral Toxicology, 2002.
25.
Fellow,
American Psychological Society (APS), 2002.
26.
Membership
in Acoustical Society of America, American Association for the Advancement of
Science, American Mathematical Society, American Psychological Association, American
Society for Engineering Education, Association for Behavior Analysis, Association
for Psychological Science, Association for Research in Vision and
Ophthalmology, Association for the Advancement of Artificial Intelligence, Cognitive
Neuroscience Society, Cognitive Science Society, European Neural Network
Society, International Neural Network Society, Memory Disorders Research
Society, New York Academy of Sciences, Optical Society of America, Psychonomic
Society, Schizophrenia International Research Society, Sigma Xi, Society for
Artificial Neural Networks in Medicine and Biology, Society for Industrial and
Applied Mathematics, Society for Mathematical Biology, Society for Mathematical
Psychology, Society for Neuroscience, SPIE, Vision Sciences Society.
27. INNS Helmholtz Award, 2003.
28. Principal Investigator
and Director, CELEST:
29. IEEE Fellow, 2005.
30. American Educational
Research Association (AERA) Fellow, 2008.
PATENTS
1. Carpenter, G.A. and Grossberg, S., U.S. Patent #5,142,590:
Pattern recognition system. Filed:
2. Carpenter, G.A. and Grossberg, S., U.S. Patent #4,914,708 and
#5,133,021: System for self- organization of stable category recognition codes
for analog patterns. Filed:
3. Carpenter, G.A. and Grossberg, S., U.S. Patent #5,311,601:
Pattern recognition system with variable selection weights. Filed:
4. Carpenter, G.A., Grossberg, S., and Reynolds,
5. Carpenter, G.A., Grossberg, S., and Rosen,
6. Grossberg, S. and Cohen,
7. Grossberg, S. and Mingolla, E., U.S. Patent #4,803,736: Neural
networks for machine vision. Filed:
LIST OF PUBLICATIONS
BOOKS
1. Editor, Mathematical psychology and
psychophysiology.
2. Studies of mind and brain: Neural
principles of learning, perception, development, cognition, and motor control.
3. Neural dynamics of adaptive sensory-motor
control: Ballistic eye movements (with M. Kuperstein).
4. The adaptive brain, I: Cognition,
learning, reinforcement, and rhythm.
5. The adaptive brain, II: Vision, speech,
language, and motor control.
6. Neural networks and natural intelligence.
7. Neural dynamics of adaptive sensory-motor
control: Expanded edition
(with M. Kuperstein).
8. Neural network models of conditioning and
action (with M.
Commons and J. Staddon).
9. Pattern recognition by self-organizing
neural networks (with G.A.
Carpenter).
10.
Neural
networks for vision and image processing (with G.A. Carpenter).
11.
Models
of neurodynamics and behavior (with J.G. Taylor).
12.
Neural
networks for automatic target recognition (with H. Hawkins and A. Waxman).
13.
Neural
control and robotics: Biology and technology (with R. Brooks and L. Optican).
14.
Spiking
neurons in neuroscience and technology (with
15.
Vision
and brain (with D. Field and L. Finkel).
ARTICLES
1. Nonlinear difference-differential
equations in prediction and learning theory. Proceedings of the
2. A prediction theory for some nonlinear
functional-differential equations, I: Learning of lists. Journal of
Mathematical Analysis and Applications, 1968, 21, 643-694.
3. A prediction theory for some nonlinear
functional-differential equations, II: Learning of patterns. Journal of
Mathematical Analysis and Applications, 1968, 22, 490-522.
4. Global ratio limit theorems for some
nonlinear functional differential equations,
5. Global ratio limit theorems for some
nonlinear functional differential equations, II. Bulletin of the American
Mathematical Society, 1968, 74, 101-105.
6. Some nonlinear networks capable of
learning a spatial pattern of arbitrary complexity. Proceedings of the
7. Some physiological and biochemical
consequences of psychological postulates. Proceedings of the
8. On the global limits and oscillations of a
system of nonlinear differential equations describing a flow of a probabilistic
network. Journal of Differential Equations, 1969, 5, 531-563.
9. On variational systems of some nonlinear
difference-differential equations. Journal of Differential Equations,
1969, 6, 544-577.
10.
Embedding
fields: A theory of learning with physiological implications. Journal of
Mathematical Psychology, 1969, 6, 209-239.
11.
On
learning, information, lateral inhibition, and transmitters. Mathematical
Biosciences, 1969, 4, 255-310.
12.
On
the production and release of chemical transmitters and related topics in
cellular control. Journal of Theoretical Biology, 1969, 22,
325-364.
13.
On
the serial learning of lists. Mathematical Biosciences, 1969, 4,
201-253.
14.
Some
networks that can learn, remember, and reproduce any number of complicated space-time
patterns,
15.
On
learning of spatiotemporal patterns by networks with ordered sensory and motor
components, I: Excitatory components of the cerebellum. Studies in Applied Mathematics, 1969, 48,
105-132.
16.
On
learning and energy-entropy dependence in recurrent and nonrecurrent signed
networks. Journal of Statistical Physics, 1969, 1, 319-350.
17.
A
global prediction (or learning) theory for some nonlinear
functional-differential equations. In J.A. Nohel (Ed.), Studies in applied
mathematics, advances in differential and integral equations, Vol. 5.
18.
Learning
and energy-entropy dependence in some nonlinear functional-differential
systems. Bulletin of the American Mathematical Society, 1969, 75,
1238-1242.
19.
Some
networks that can learn, remember, and reproduce any number of complicated
space-time patterns, II. Studies in Applied Mathematics, 1970, 49,
135-166.
20.
Neural
pattern discrimination. Journal of Theoretical Biology, 1970, 27,
291-337.
21.
Schizophrenia:
Possible dependence of associational span, bowing, and primacy vs. recency on
spiking threshold (with J. Pepe). Behavioral Science, 1970, 15,
359-362.
22.
Embedding
fields: Underlying philosophy, mathematics, and applications to psychology,
physiology, and anatomy. Journal of Cybernetics, 1971, 1, 28-50.
23.
Spiking
threshold and overarousal effects in serial learning (with J. Pepe). Journal
of Statistical Physics, 1971, 3, 95-125.
24.
Functional-differential
systems and pattern learning. In D. Chillingsworth (Ed.), Lecture notes in
mathematics, Vol. 206.
25.
On
the dynamics of operant conditioning. Journal of Theoretical Biology,
1971, 33, 225-255.
26.
Pavlovian
pattern learning by nonlinear neural networks. Proceedings of the
27.
Neural
expectation: Cerebellar and retinal analogs of cells fired by learnable or
unlearned pattern classes. Kybernetik, 1972, 10, 49-57.
28.
A
neural theory of punishment and avoidance, I: Qualitative theory. Mathematical
Biosciences, 1972, 15, 39-67.
29.
A
neural theory of punishment and avoidance, II: Quantitative theory. Mathematical
Biosciences, 1972, 15, 253-285.
30.
Pattern
learning by functional-differential neural networks with arbitrary path
weights. In K. Schmitt (Ed.), Delay and functional-differential equations
and their applications.
31.
Contour
enhancement, short-term memory, and constancies in reverberating neural
networks. Studies in Applied Mathematics, 1973, 52, 217-257.
32.
Classical
and instrumental learning by neural networks. In R. Rosen and F. Snell (Eds.), Progress
in theoretical biology.
33.
A
neural model of attention, reinforcement, and discrimination learning. International
Review of Neurobiology, 1975, 18, 263-327.
34.
Some
developmental and attentional biases in the contrast enhancement and short-term
memory of recurrent neural networks (with D. Levine). Journal of Theoretical
Biology, 1975, 53, 341-380.
35.
Pattern
formation, contrast control, and oscillations in the short-term memory of
shunting on-center off-surround networks (with S.A. Ellias). Biological
Cybernetics, 1975, 20, 69-98.
36.
On
the development of feature detectors in the visual cortex with applications to
learning and reaction-diffusion systems. Biological Cybernetics, 1976, 21,
145-159.
37.
On
visual illusions in neural networks: Line neutralization, tilt aftereffect, and
angle expansion (with D. Levine). Journal of Theoretical Biology, 1976, 61,
477-504.
38.
Adaptive
pattern classification and universal recoding, I: Parallel development and
coding of neural feature detectors. Biological Cybernetics, 1976, 23,
121-134.
39.
Adaptive
pattern classification and universal recoding, II: Feedback, expectation,
olfaction, and illusions. Biological Cybernetics, 1976, 23,
187-202.
40.
Redundant
information in auditory and visual modalities: Inferring decision-related
processes from the P300 component (with
41.
Pattern
formation by the global limits of a nonlinear competitive interaction in n
dimensions. Journal of Mathematical Biology, 1977, 4, 237-256.
42.
A
theory of human memory: Self-organization and performance of sensory-motor
codes, maps, and plans. In R. Rosen and F. Snell (Eds.), Progress in
theoretical biology, Volume 5.
43.
Communication,
memory, and development. In R. Rosen and F. Snell (Eds.), Progress in
theoretical biology, Volume 5.
44.
A
theory of visual coding, memory, and development. In E. Leeuwenberg and H.
Buffart (Eds.), Formal theories of visual perception.
45.
Behavioral
contrast in short-term memory: Serial binary memory models or parallel
continuous memory models? Journal of Mathematical Psychology, 1978, 3,
199-219.
46.
Competition,
decision, and consensus. Journal of Mathematical Analysis and Applications,
1978, 66, 470-493.
47.
Do
all neural models really look alike? Psychological Review, 1978, 85,
592-596.
48.
Decisions,
patterns, and oscillations in nonlinear competitive systems with applications
to Volterra-Lotka systems. Journal of Theoretical Biology, 1978, 73,
101-130.
49.
Adaptive
pattern classification and universal recoding: Parallel development and coding
of neural feature detectors. In R. Trappl (Ed.), Third European conference
on cybernetics and systems research.
50.
How
does a brain build a cognitive code? Psychological Review, 1980, 87,
1-51.
51.
Biological
competition: Decision rules, pattern formation, and oscillations. Proceedings
of the
52.
Intracellular
mechanisms of adaptation and self-regulation in self-organizing networks: The
role of chemical transducers. Bulletin of Mathematical Biology, 1980, 42,
365-396.
53.
Human
and computer rules and representations are not equivalent. Behavioral and
Brain Sciences, 1980, 3, 136-138.