User:Jrcrin001/sandbox
Professor Gail Alexandra Carpenter 2005 picture | |
|---|---|
| Born | 1948 (Age 73 in 2022) New York City, New York, USA |
| Citizenship | American |
| Alma mater | University of Wisconsin–Madison University of Colorado-Boulder |
| Known for | Adaptive Resonance Theory (ART), neural network models and applications |
| Spouse(s) | Stephen Grossberg (m. 1979 -) |
| Children | 1 |
| Awards | IEEE Neural Networks Pioneer (2008) |
| Scientific career | |
| Fields | Mathmatics, Neuroscience |
| Institutions | Boston University, Northeastern University, MIT |
| Academic advisors | Charles C. Conley |
Gail Alexandra Carpenter, Ph.d (born in 1948) is a cognitive scientist, neuroscientist and mathematician. She is now a "Professor Emerita of Mathematics and Statistics, Boston University."[1] She had also been a Professor of Cognitive and Neural Systems at Boston University, and the director of the Department of Cognitive and Neural Systems (CNS) Technology Lab at Boston University.[2][3]
Early Life
[edit]Gail Carpenter is the only daughter of Chadwick Hunter "Chad" Carpenter (1920-1996) and Ruth M. (nee Stevenson) Carpenter (1920-2010). She has four brothers.[4])[5]
Carpenter attended the International School of Geneva (1961-1966) then went to the University of Colorado in Boulder earning a B.A. in 1970 (summa cum laude, mathematics). She then earned a Ph.D. in mathematics at the University of Wisconsin–Madison. Carpenter then taught at MIT and Northeastern University before moving to Boston University.[6][2]
Carpenter married Stephen Grossberg on June 16, 1979 in Boston University Castle in Boston, Massachusetts.[7]
Adaptive resonance theory
[edit]Carpenter's neural modeling work began with her 1974 mathematics PhD thesis, Traveling wave solutions of nerve impulse equations at the University of Wisconsin Department of Mathmatics working with Charles C. Conley. In a series of papers published in the 1970s, she defined generalized Hodgkin-Huxley models, used dynamical systems techniques to analyze their solutions, and characterized the qualitative properties of the burst suppression patterns that a typical neuron may propagate and investigated normal and abnormal signal patterns in nerve cells.[6]
Together with her students and colleagues, Carpenter has since the 1980s, developed the adaptive resonance theory (ART) family of neural networks for fast stable online learning, pattern recognition, and prediction. ART models have been used for a wide range of applications, including remote sensing, medical diagnosis, automatic target recognition, mobile robots, and database management.[2]
Other aspects of her research include the development, computational analysis, and application of neural models of vision, synaptic transmission, and circadian rhythms. Her work in vision ranges from models of photoreceptors to color processing and long-range figure completion][2]
At Boston University, she served as founder and director of the CNS Technology Lab and as a founding member of the Center for Adaptive Systems and the Department of Cognitive and Neural Systems.[2]
Adaptive resonance theory (ART) is a theory developed by Stephen Grossberg and Gail Carpenter on aspects of how the brain processes information. It describes a number of neural network models which use supervised and unsupervised learning methods, and address problems such as pattern recognition and prediction.[8]
The primary intuition behind the ART model is that object identification and recognition generally occur as a result of the interaction of 'top-down' observer expectations with 'bottom-up' sensory information. The model postulates that 'top-down' expectations take the form of a memory template or prototype that is then compared with the actual features of an object as detected by the senses. This comparison gives rise to a measure of category belongingness. As long as this difference between sensation and expectation does not exceed a set threshold called the 'vigilance parameter', the sensed object will be considered a member of the expected class. The system thus offers a solution to the 'plasticity/stability' problem, i.e. the problem of acquiring new knowledge without disrupting existing knowledge that is also called incremental learning. [8]
Academic acknowledgements
[edit]She was the first woman to receive the Institute of Electrical and Electronics Engineers (IEEE) Neural Networks Pioneer Award in 2008. She has been elected to successive three-year terms on the Board of Governors of the International Neural Network Society (INNS)[9]) since its founding, in 1987, and received the INNS Gabor Award in 1999. She has also served as an elected member of the Council of the American Mathematical Society, and is a charter member of the Association for Women in Mathematics.[2]
Additional awards and honors include:
Institute of Electrical and Electronics Engineers
IEEE Fellow Award (2013)
IEEE Senior Membership Award (2011)
IEEE Neural Networks Pioneer Award (2008)
International Neural Network Society
INNS Fellow Award (2011)
College of Fellows (2011 – )
Governing Board (1987–2010)
Secretary & Executive Committee (1994–2000)
Vice President (1988 1989)
American Mathematical Society
AMS Council – Member at Large (1996–1999)
Committee on the Profession (1996–1999)
Liaison Committee with AAAS (2004–2006)
Editorial Boards
Brain Research
IEEE Transactions on Neural Networks
Neural Networks
Biologically Inspired Cognitive Architectures
Memberships
American Mathematical Society (AMS)
Association for Women in Mathematics (AWM)
Institute of Electrical and Electronics Engineers (IEEE)
IEEE Computational Intelligence Society
International Neural Network Society (INNS)
Published articles include
[edit]Carpenter, G. A. (2019). Looking to the future: Learning from experience, averting catastrophe. Neural Networks.
Carpenter, G. A., & Grossberg, S. (1987). A massively parallel architecture for a self-organizing neural pattern recognition machine. Computer Vision, Graphics and Image Processing, 37(1), 54–115. https://doi.org/10.1016/S0734-189X(87)80014-2
Carpenter, G. A., Grossberg, S., Markuzon, N., Reynolds, J. H., & Rosen, D. B. (1992). Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Maps. IEEE Transactions on Neural Networks, 3(5), 698–713. https://doi.org/10.1109/72.159059
Carpenter, G. A., Grossberg, S., & Reynolds, J. H. (1991). ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network. Neural Networks, 4(5), 565–588. https://doi.org/10.1016/0893-6080(91)90012-T
Carpenter, G. A., Grossberg, S., & Rosen, D. B. (1991). Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system. Neural Networks, 4(6), 759–771. https://doi.org/10.1016/0893-6080(91)90056-B
See also
[edit]The INNS (International Neural Network Society) history project has been documenting the experiences of pioneers of the INNS field: You Tube video interview with Gail Carpenter,
Recorded January 14, 2021. See also INNS History Project.
Article Search Results (48) from the Boston University web page for Gail Carpenter. Click here.
Carpenter is also cited in the following book:
American Men & Women of Science[10]
References
[edit]- ^ Google Scholar
- ^ a b c d e f https://en-academic.com/dic.nsf/enwiki/11272893%7C Academic Dictionaries and Encyclopedias| Access Date 18 January 2022
- ^ https://mailman.srv.cs.cmu.edu/pipermail/connectionists/1989-December/012034.html |Wang Institute Conference| 1990 bio|
GAIL CARPENTER is Professor of Mathematics and CNS; Co-Director of the
CNS Graduate Program; 1989 Vice President of the International Neural Network
Society (INNS); Organization Chairman of the 1988 INNS annual meeting; Session Chairman at the 1989 and 1990 IEEE/INNS International Joint Conference on Neural Networks (IJCNN); one of four technical consultants to the national DARPA Neural Network Study; editor of the journals "Neural Networks", "Neural Computation", and "Neural Network Review"; and a member of the scientific advisory board of HNC. A leading neural architect, Carpenter is especially well-known for her seminal work on developing the adaptive resonance theory architectures (ART 1, ART 2, ART 3) for adaptive pattern recognition. - ^ https://www.ancestry.com/discoveryui-content/view/653020371:61843 | Obituary for Ruth S. Carpenter| Accessed 18 January 2022| See also: April 29, 1947 Marriage at: https://www.ancestry.com/discoveryui-content/view/2268275:61406
- ^ https://www.ancestry.com/discoveryui-content/view/613063443:61843%7C Ancestry.com result for Chadwick Hunter Carpenter obit| Accessed 18 January 2022
- ^ a b https//techlab.bu.edu/members/gail/| CNS Technology Website| Accessed 18 January 2022
- ^ Newspapers.com| The Jackson Hole Guide; Publication Date: 21/ Jun/ 1979; Publication Place: Jackson, Wyoming, USA; URL: https://www.newspapers.com/image/317801978/?article=793bcdc8-8859-426f-a1ad-06890f4299c4&focus=0.036960505,0.094845355,0.2794417,0.50327265&xid=3398
- ^ a b Carpenter, G.A., Grossberg, S., & Reynolds, J.H. (1991), ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network Archived 2006-05-19 at the Wayback Machine, Neural Networks, 4, 565-588
- ^ https://www.inns.org/%7C International Neural Network Society (INNS)| Accessed 18 January 2022
- ^ ’’American Men & Women of Science.’’ A biographical directory of today's leaders in physical, biological and related sciences. 23rd edition. Eight volumes. Detroit: Thomson Gale, 2006. (AmMWSc 23)
Category:1948 births
Category:Living people
Category:Cognitive scientists
Category:Boston University faculty
Category:20th-century American mathematicians
Category:21st-century American mathematicians
Category:University of Colorado alumni
Category:University of Wisconsin–Madison College of Letters and Science alumni
Category:Northeastern University faculty
Category:International School of Geneva alumni