Dávid Nagy

1.1k citations
51 papers · 822 · h-index 17

Impact in

Papers in

Dávid Nagy

46 papers receiving 806 citations

Peers

Dávid Nagy
Comparison fields: 5 of 99
  • Atomic and Molecular Physics, and Optics 369
  • Biological Psychiatry 25
  • Behavioral Neuroscience 29
  • Cellular and Molecular Neuroscience 126
  • Artificial Intelligence 232
Replace Evan A. Thomas with:
Evan A. Thomas Australia
Ivan I. Maximov Norway
Alvin H. Bachman United States
Jennifer Ahjin Kim United States
Benjamin A.E. Hunt United Kingdom
Hisashi Aikawa Japan
William J. Eckner United States
Gerald Cooray Sweden
Shaolin Yang United States
Carsten Krogh Nielsen Denmark
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Citations per field
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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 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011108
2 201675
3 200953
4 199750
5 201549
6 201042
7 200634
8 200833
9 202233
10 202231
11 200931
12 200931
13 201123
14 200719
15 201417
16 201917
17 200817
18 201216
19 201616
20 201215

About Dávid Nagy

Dávid Nagy is a scholar working on Cellular and Molecular Neuroscience, Atomic and Molecular Physics, and Optics, Cardiology and Cardiovascular Medicine, Artificial Intelligence and Spectroscopy, having authored 51 papers that have together received 822 indexed citations. Recurring topics across this work include Cold Atom Physics and Bose-Einstein Condensates (12 papers), Neuroscience and Neuropharmacology Research (8 papers), Quantum Information and Cryptography (6 papers), Mechanical and Optical Resonators (4 papers), Strong Light-Matter Interactions (4 papers), Memory and Neural Mechanisms (3 papers), Cardiac Fibrosis and Remodeling (3 papers) and SARS-CoV-2 and COVID-19 Research (3 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (369 citations), Biological Psychiatry (25 citations), Behavioral Neuroscience (29 citations), Cellular and Molecular Neuroscience (126 citations) and Artificial Intelligence (232 citations). Dávid Nagy has collaborated with scholars based in Hungary, United States and Germany. Frequent co-authors include P. Domokos, Gergely Szirmai, Helmut Ritsch, Tamás Farkas, Zsolt Kis, József Toldi, László Vécsei, András Vukics, Vivian I. Teichberg and Máté Marosi. Their work appears in journals such as Physical Review A, European Heart Journal, Physical Review Letters, Frontiers in Immunology and European Biophysics 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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