Daniel S. Levine

4.0k total citations · 1 hit paper
123 papers, 2.4k citations indexed

About

Daniel S. Levine is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Social Psychology. According to data from OpenAlex, Daniel S. Levine has authored 123 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Cognitive Neuroscience, 26 papers in Artificial Intelligence and 13 papers in Social Psychology. Recurrent topics in Daniel S. Levine's work include Neural dynamics and brain function (23 papers), Neural Networks and Applications (15 papers) and Neural and Behavioral Psychology Studies (15 papers). Daniel S. Levine is often cited by papers focused on Neural dynamics and brain function (23 papers), Neural Networks and Applications (15 papers) and Neural and Behavioral Psychology Studies (15 papers). Daniel S. Levine collaborates with scholars based in United States, Canada and China. Daniel S. Levine's co-authors include Stephen Grossberg, Peter Skippen, Douglas G. Matsell, Helen Nadel, Jean‐Paul Collet, Cherry Mammen, Leonid Perlovsky, Morton E. Gurtin, Frank L. Lewis and Riane Eisler and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and Journal of Consulting and Clinical Psychology.

In The Last Decade

Daniel S. Levine

114 papers receiving 2.2k citations

Hit Papers

Long-term Risk of CKD in Children Surviving Episodes of A... 2011 2026 2016 2021 2011 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel S. Levine United States 25 817 460 357 225 190 123 2.4k
Warren S. Brown United States 46 2.7k 3.3× 385 0.8× 275 0.8× 473 2.1× 531 2.8× 135 6.0k
L. Harrison United Kingdom 13 3.2k 3.9× 208 0.5× 311 0.9× 16 0.1× 467 2.5× 38 4.3k
Georg Dorffner Austria 33 1.8k 2.3× 804 1.7× 32 0.1× 39 0.2× 891 4.7× 138 4.0k
Amy E. Taylor United Kingdom 35 180 0.2× 44 0.1× 47 0.1× 298 1.3× 384 2.0× 95 6.1k
F. Eugene Yates United States 30 294 0.4× 89 0.2× 35 0.1× 62 0.3× 83 0.4× 68 2.9k
Guillaume Dumas France 34 2.9k 3.5× 106 0.2× 128 0.4× 15 0.1× 466 2.5× 167 4.9k
James W. Roberts United States 34 354 0.4× 121 0.3× 18 0.1× 69 0.3× 54 0.3× 183 4.2k
Jonathan Kirsch United States 19 364 0.4× 118 0.3× 132 0.4× 21 0.1× 30 0.2× 59 2.0k
Stephanie Seneff United States 36 212 0.3× 3.6k 7.8× 43 0.1× 25 0.1× 293 1.5× 253 5.7k
Bert F. Green United States 25 364 0.4× 566 1.2× 10 0.0× 120 0.5× 380 2.0× 63 4.0k

Countries citing papers authored by Daniel S. Levine

Since Specialization
Citations

This map shows the geographic impact of Daniel S. Levine'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 Daniel S. Levine with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel S. Levine more than expected).

Fields of papers citing papers by Daniel S. Levine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel S. Levine. 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 Daniel S. Levine. The network helps show where Daniel S. Levine may publish in the future.

Co-authorship network of co-authors of Daniel S. Levine

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel S. Levine. A scholar is included among the top collaborators of Daniel S. Levine based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel S. Levine. Daniel S. Levine is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Levine, Daniel S.. (2021). Mind and Heart As Partners. 8(1). 9–9. 1 indexed citations
2.
Levine, Daniel S.. (2019). One or two minds? Neural network modeling of decision making by the unified self. Neural Networks. 120. 74–85. 8 indexed citations
3.
Song, Ruizhuo, Frank L. Lewis, Qinglai Wei, et al.. (2015). Multiple Actor-Critic Structures for Continuous-Time Optimal Control Using Input-Output Data. IEEE Transactions on Neural Networks and Learning Systems. 26(4). 851–865. 116 indexed citations
4.
Levine, Daniel S., et al.. (2015). A neural network model of decisions on the Asian Disease Problem. 7. 1–8. 5 indexed citations
5.
Levine, Daniel S., et al.. (2013). A review of the certainty effect and influence of information processing. SHILAP Revista de lepidopterología. 1 indexed citations
6.
Levine, Daniel S.. (2013). Neural Networks for Knowledge Representation and Inference. Psychology Press eBooks. 5 indexed citations
7.
Farajidavar, Aydin, Daniel S. Levine, Nicholas W. Kohn, & Paul B. Paulus. (2010). Modeling the beneficial effects of incubation in creative brainstorming. 1–6.
8.
Levine, Daniel S.. (2008). Neural networks of human nature and nurture. SHILAP Revista de lepidopterología. 3 indexed citations
9.
Huang, De-Shuang, Donald C. Wunsch, Daniel S. Levine, & Kang-Hyun Jo. (2008). Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence: Fourth International Conference on Intelligent Computing. 1251–1251. 2 indexed citations
10.
Huang, De-Shuang, Donald C. Wunsch, Daniel S. Levine, & Kang-Hyun Jo. (2008). Advanced Intelligent Computing Theories and Applications With Aspects of Contemporary Intelligent Computing Techniques: 4th International Conference on ... in Computer and Information Science). Springer eBooks. 1 indexed citations
11.
Levine, Daniel S., Jonathan Akikusa, David Manson, Earl D. Silverman, & Rayfel Schneider. (2006). Chest CT findings in pediatric Wegener’s granulomatosis. Pediatric Radiology. 37(1). 57–62. 15 indexed citations
12.
Sonsino, Doron, Ido Erev, David V. Budescu, et al.. (2001). On Rationality, Learning and Zero-Sum Betting - An Experimental Study of the No-Betting Conjecture. 17. 98–98. 25 indexed citations
13.
Levine, Daniel S.. (1998). Disease: neural network models. MIT Press eBooks. 315–318. 1 indexed citations
14.
Levine, Daniel S.. (1990). ART 1.5 - A Simplified Adaptive Resonance Network for Classifying Low-dimensional Analog Data. Medical Entomology and Zoology. 2. 639–642. 12 indexed citations
15.
Levine, Daniel S. & Raju S. Bapi. (1990). Networks modeling the involvement of the frontal lobes in learning and performance of flexible movement sequences. eScholarship (California Digital Library). 759–764 vol.2. 3 indexed citations
16.
Levine, Daniel S.. (1989). The third wave in neural networks. 4(12). 26–30. 4 indexed citations
17.
Cohen, Michael A. & Daniel S. Levine. (1985). Unbounded Oscillatory Solutions for a System of Interacting Populations. SIAM Journal on Applied Mathematics. 45(2). 268–279. 3 indexed citations
18.
Levine, Daniel S.. (1983). Bifurcating periodic solutions for a class of age-structured predator-prey systems. Bulletin of Mathematical Biology. 45(6). 901–915. 7 indexed citations
19.
Gurtin, Morton E. & Daniel S. Levine. (1979). On predator-prey interactions with predation dependent on age of prey. Mathematical Biosciences. 47(3-4). 207–219. 53 indexed citations
20.
Levine, Daniel S., et al.. (1968). Computer aided design of linear and saturating servomechanisms. IEEE Transactions on Automatic Control. 6(6). 565–571. 1 indexed citations

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.

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