Daniel S. Levine

4.1k citations
137 papers · 2.8k · h-index 27

Impact in

Papers in

    • Neural dynamics and brain function 26
    • Neural and Behavioral Psychology Studies 21
    • Cognitive Science and Education Research 15
    • Memory and Neural Mechanisms 9
    • Neural Networks and Applications 16
    • Cognitive Science and Mapping 16

Daniel S. Levine

125 papers receiving 2.6k citations

Peers

Daniel S. Levine
Comparison fields: 5 of 176
  • General Decision Sciences 116
  • Nephrology 357
  • Cognitive Neuroscience 1.0k
  • Experimental and Cognitive Psychology 234
  • Artificial Intelligence 609
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Citations per field
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Citations per year

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-authors

The 25 scholars most cited alongside Daniel S. Levine, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel S. Levine Line = papers co-authored together Daniel S. Levine links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 137 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011420
2 1987248
3 1975130
4 1989128
5 2015126
6 200091
7 197676
8 198374
9 200673
10 197967
11 200856
12 200254
13 199551
14 200949
15 200649
16 198347
17 198247
18 198145
19 201044
20 198843

About Daniel S. Levine

Daniel S. Levine is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Public Health, Environmental and Occupational Health, Social Psychology and Experimental and Cognitive Psychology, having authored 137 papers that have together received 2.8k indexed citations. Recurring topics across this work include Neural dynamics and brain function (26 papers), Neural and Behavioral Psychology Studies (21 papers), Neural Networks and Applications (16 papers), Cognitive Science and Mapping (16 papers), Cognitive Science and Education Research (15 papers), Mathematical and Theoretical Epidemiology and Ecology Models (12 papers), Decision-Making and Behavioral Economics (11 papers) and Memory and Neural Mechanisms (9 papers). The work is most often cited by research in General Decision Sciences (116 citations), Nephrology (357 citations), Cognitive Neuroscience (1.0k citations), Experimental and Cognitive Psychology (234 citations) and Artificial Intelligence (609 citations). Daniel S. Levine has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Stephen Grossberg, Helen Nadel, Jean‐Paul Collet, Peter Skippen, Cherry Mammen, Douglas G. Matsell, Morton E. Gurtin, Leonid Perlovsky, Frank L. Lewis and Riane Eisler. Their work appears in journals such as Neural Networks, Mathematical Biosciences, Behavioral and Brain Sciences, Bulletin of Mathematical Biology and Neurocomputing.

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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