Dávid Nagy

1.1k citations
48 papers · 761 · h-index 16

Impact in

Papers in

Dávid Nagy

44 papers receiving 751 citations

Peers

Dávid Nagy
Comparison fields: 5 of 94
  • Atomic and Molecular Physics, and Optics 349
  • Biological Psychiatry 21
  • Behavioral Neuroscience 26
  • Artificial Intelligence 223
  • Cellular and Molecular Neuroscience 121
Replace Travis J. A. Craddock with:
Travis J. A. Craddock United States
Thomas R. Wood United States
Yu Watanabe Japan
Ai‐Xia Zhang China
William J. Eckner United States
Ivan I. Maximov Norway
Evan A. Thomas Australia
Alvin H. Bachman United States
Neil P. Oxtoby United Kingdom
Hisashi Aikawa Japan
Dávid Nagy relative to Travis J. A. Craddock United States Travis J. A. Craddock's profile →
Citations per field
00.5×6.4×
Travis J. A. Craddock · 1×
Citations per year

Countries citing papers authored by Dávid Nagy

Since Specialization
Citations

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

Fields of papers citing papers by Dávid Nagy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dávid Nagy. 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 Dávid Nagy. The network helps show where Dávid Nagy may publish in the future.

Co-authors

The 25 scholars most cited alongside Dávid Nagy, 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 Dávid Nagy Line = papers co-authored together Dávid Nagy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011104
2 201670
3 200948
4 201545
5 199744
6 201040
7 200633
8 200832
9 202231
10 202230
11 200930
12 200929
13 201123
14 200719
15 201217
16 201416
17 200815
18 201915
19 201615
20 201213

About Dávid Nagy

Dávid Nagy is a scholar working on Atomic and Molecular Physics, and Optics, Cellular and Molecular Neuroscience, Molecular Biology, Artificial Intelligence and Cardiology and Cardiovascular Medicine, having authored 48 papers that have together received 761 indexed citations. Recurring topics across this work include Cold Atom Physics and Bose-Einstein Condensates (11 papers), Neuroscience and Neuropharmacology Research (8 papers), Quantum Information and Cryptography (6 papers), Strong Light-Matter Interactions (4 papers), Cardiac Fibrosis and Remodeling (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Memory and Neural Mechanisms (3 papers) and Mechanical and Optical Resonators (3 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (349 citations), Biological Psychiatry (21 citations), Behavioral Neuroscience (26 citations), Artificial Intelligence (223 citations) and Cellular and Molecular Neuroscience (121 citations). Dávid Nagy has collaborated with scholars based in Hungary, Switzerland and Germany. Frequent co-authors include P. Domokos, G. Szirmai, Helmut Ritsch, Tamás Farkas, József Toldi, Zsolt Kis, László Vécsei, András Vukics, Máté Marosi and Vivian I. Teichberg. Their work appears in journals such as Physical Review A, Physical review. A, Microchemical Journal, European Biophysics Journal and European Heart Journal.

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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