Steven E. Hampson
Impact in
- Artificial Intelligence top 10%
- Neural Networks and Applications
- Machine Learning and Algorithms
- Evolutionary Algorithms and Applications
- Machine Learning and Data Classification
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- Neural dynamics and brain function
Papers in
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- Neural Networks and Applications 10
- Fuzzy Logic and Control Systems 4
- Machine Learning and Algorithms 3
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- Neural dynamics and brain function 5
- Co-authors
- Dennis Kibler (4 shared papers)Pierre Baldi (2 shared papers)D. W. Rains (2 shared papers)R. S. Loomis (2 shared papers)Yung‐Hsiang Chen (1 shared paper)Yuexin Shan (1 shared paper)Tsun-Jui Liu (1 shared paper)Ping H. Wang (1 shared paper)
- Journals
- Biological Cybernetics (5 papers)PLANT PHYSIOLOGY (2 papers)Progress in Neurobiology (2 papers)Circulation Research (1 paper)Bioinformatics (1 paper)
- Partner nations
- United StatesTaiwan
In The Last Decade
Steven E. Hampson
17 papers receiving 278 citations
Peers
Comparison fields: 5 of 78
- Artificial Intelligence 140
- Cognitive Neuroscience 49
- Signal Processing 18
- Plant Science 58
- Molecular Biology 97
Countries citing papers authored by Steven E. Hampson
This map shows the geographic impact of Steven E. Hampson's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Steven E. Hampson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven E. Hampson more than expected).
Fields of papers citing papers by Steven E. Hampson
This network shows the impact of papers produced by Steven E. Hampson. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Steven E. Hampson. The network helps show where Steven E. Hampson may publish in the future.
Co-authors
The 8 scholars most cited alongside Steven E. Hampson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1986 | 48 | |
| 2 | 2003 | 38 | |
| 3 | 2002 | 36 | |
| 4 | 1983 | 34 | |
| 5 | 1978 | 27 | |
| 6 | 2004 | 20 | |
| 7 | 1987 | 20 | |
| 8 | 1990 | 19 | |
| 9 | 1987 | 17 | |
| 10 | 1990 | 13 | |
| 11 | A neural model of adaptive behavior | 1983 | 13 |
| 12 | 1986 | 10 | |
| 13 | 1978 | 9 | |
| 14 | 1990 | 9 | |
| 15 | 1991 | 7 | |
| 16 | 1994 | 1 | |
| 17 | 1999 | 1 |
About Steven E. Hampson
Steven E. Hampson is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Molecular Biology, Plant Science and Control and Systems Engineering, having authored 17 papers that have together received 322 indexed citations. Recurring topics across this work include Neural Networks and Applications (10 papers), Neural dynamics and brain function (5 papers), Fuzzy Logic and Control Systems (4 papers), Machine Learning and Algorithms (3 papers), Machine Learning in Bioinformatics (2 papers), Genomics and Chromatin Dynamics (2 papers), Research in Cotton Cultivation (2 papers) and Face and Expression Recognition (1 paper). The work is most often cited by research in Artificial Intelligence (140 citations), Cognitive Neuroscience (49 citations), Signal Processing (18 citations), Plant Science (58 citations) and Molecular Biology (97 citations). Steven E. Hampson has collaborated with scholars based in United States and Taiwan. Frequent co-authors include Dennis Kibler, Pierre Baldi, D. W. Rains, R. S. Loomis, Yung‐Hsiang Chen, Yuexin Shan, Tsun-Jui Liu and Ping H. Wang. Their work appears in journals such as Biological Cybernetics, PLANT PHYSIOLOGY, Progress in Neurobiology, Circulation Research and Bioinformatics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.