Máté Nagy

2.6k total citations · 1 hit paper
33 papers, 1.8k citations indexed

About

Máté Nagy is a scholar working on Ecology, Evolution, Behavior and Systematics, Genetics and Computer Networks and Communications. According to data from OpenAlex, Máté Nagy has authored 33 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Ecology, Evolution, Behavior and Systematics, 9 papers in Genetics and 8 papers in Computer Networks and Communications. Recurrent topics in Máté Nagy's work include Animal Behavior and Reproduction (13 papers), Insect and Arachnid Ecology and Behavior (6 papers) and Distributed Control Multi-Agent Systems (6 papers). Máté Nagy is often cited by papers focused on Animal Behavior and Reproduction (13 papers), Insect and Arachnid Ecology and Behavior (6 papers) and Distributed Control Multi-Agent Systems (6 papers). Máté Nagy collaborates with scholars based in Hungary, Germany and United Kingdom. Máté Nagy's co-authors include Tamás Vicsek, Dora Biro, Zsuzsa Ákos, Iain D. Couzin, Gábor Vásárhelyi, Liang Li, I. Daruka, Jacob M. Graving, Benjamin Pettit and Joseph B. Bak-Coleman and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Máté Nagy

33 papers receiving 1.8k citations

Hit Papers

Hierarchical group dynamics in pigeon flocks 2010 2026 2015 2020 2010 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Máté Nagy Hungary 19 465 447 307 280 246 33 1.8k
Hanno Hildenbrandt Netherlands 24 347 0.7× 563 1.3× 259 0.8× 208 0.7× 203 0.8× 40 1.9k
E. Cisbani Italy 10 633 1.4× 390 0.9× 261 0.9× 405 1.4× 140 0.6× 86 2.0k
Raphaël Candelier France 16 640 1.4× 438 1.0× 272 0.9× 546 1.9× 109 0.4× 24 2.6k
Alberto Orlandi Italy 7 714 1.5× 507 1.1× 336 1.1× 448 1.6× 113 0.5× 8 2.0k
Zsuzsa Ákos Hungary 8 284 0.6× 328 0.7× 190 0.6× 126 0.5× 106 0.4× 10 1.1k
Andrea Procaccini Italy 10 715 1.5× 508 1.1× 436 1.4× 452 1.6× 113 0.5× 12 2.3k
Jacques Gautrais France 30 514 1.1× 862 1.9× 771 2.5× 239 0.9× 84 0.3× 65 3.1k
José Halloy France 24 469 1.0× 367 0.8× 359 1.2× 110 0.4× 146 0.6× 68 2.2k
Kolbjørn Tunstrøm Sweden 8 348 0.7× 309 0.7× 163 0.5× 322 1.1× 65 0.3× 10 1.1k
Daniel Grünbaum United States 29 738 1.6× 615 1.4× 468 1.5× 335 1.2× 119 0.5× 65 3.4k

Countries citing papers authored by Máté Nagy

Since Specialization
Citations

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

Fields of papers citing papers by Máté Nagy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Máté Nagy

This figure shows the co-authorship network connecting the top 25 collaborators of Máté Nagy. A scholar is included among the top collaborators of Máté Nagy 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 Máté Nagy. Máté Nagy 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.
Li, Liang, Máté Nagy, Wei Wang, et al.. (2025). Reverse engineering the control law for schooling in zebrafish using virtual reality. Science Robotics. 10(101). eadq6784–eadq6784. 2 indexed citations
2.
Naik, Hemal, Máté Nagy, Iain D. Couzin, et al.. (2024). 3D-MuPPET: 3D Multi-Pigeon Pose Estimation and Tracking. International Journal of Computer Vision. 132(10). 4235–4252. 8 indexed citations
3.
Sampaio, Eduardo, Vivek H. Sridhar, Máté Nagy, et al.. (2024). Multidimensional social influence drives leadership and composition-dependent success in octopus–fish hunting groups. Nature Ecology & Evolution. 8(11). 2072–2084. 3 indexed citations
4.
Li, Liang, et al.. (2024). Revealing the mechanism and function underlying pairwise temporal coupling in collective motion. Nature Communications. 15(1). 4356–4356. 10 indexed citations
5.
Nagy, Máté, Jacob D. Davidson, Gábor Vásárhelyi, et al.. (2024). Long-term tracking of social structure in groups of rats. Scientific Reports. 14(1). 22857–22857. 2 indexed citations
6.
Fülöp, Attila, et al.. (2023). Fine-scale collective movements reveal present, past and future dynamics of a multilevel society in Przewalski’s horses. Nature Communications. 14(1). 5096–5096. 14 indexed citations
7.
Sridhar, Vivek H., et al.. (2023). Inferring social influence in animal groups across multiple timescales. Philosophical Transactions of the Royal Society B Biological Sciences. 378(1874). 20220062–20220062. 7 indexed citations
8.
Nagy, Máté, Hemal Naik, Fumihiro Kano, et al.. (2023). SMART-BARN: Scalable multimodal arena for real-time tracking behavior of animals in large numbers. Science Advances. 9(35). eadf8068–eadf8068. 17 indexed citations
9.
Kano, Fumihiro, et al.. (2022). Head-tracking of freely-behaving pigeons in a motion-capture system reveals the selective use of visual field regions. Scientific Reports. 12(1). 19113–19113. 16 indexed citations
10.
Sridhar, Vivek H., Liang Li, Dan Gorbonos, et al.. (2021). The geometry of decision-making in individuals and collectives. Proceedings of the National Academy of Sciences. 118(50). 67 indexed citations
11.
Li, Liang, Máté Nagy, Jacob M. Graving, et al.. (2020). Vortex phase matching as a strategy for schooling in robots and in fish. Nature Communications. 11(1). 5408–5408. 151 indexed citations
12.
Nagy, Máté, Enikő Kubinyi, Iain D. Couzin, et al.. (2020). Synergistic Benefits of Group Search in Rats. Current Biology. 30(23). 4733–4738.e4. 21 indexed citations
13.
Marcelino, Rui, et al.. (2020). Collective movement analysis reveals coordination tactics of team players in football matches. Chaos Solitons & Fractals. 138. 109831–109831. 46 indexed citations
14.
Klein, Karsten, Björn Sommer, Hieu T. Nim, et al.. (2019). Fly with the flock: immersive solutions for animal movement visualization and analytics. Journal of The Royal Society Interface. 16(153). 20180794–20180794. 20 indexed citations
15.
Mizuguchi, Tsuyoshi, et al.. (2015). Coordinated Behaviour in Pigeon Flocks. PLoS ONE. 10(10). e0140558–e0140558. 20 indexed citations
16.
Ákos, Zsuzsa, Robert E. Beck, Máté Nagy, Tamás Vicsek, & Enikő Kubinyi. (2014). Leadership and Path Characteristics during Walks Are Linked to Dominance Order and Individual Traits in Dogs. PLoS Computational Biology. 10(1). e1003446–e1003446. 51 indexed citations
17.
Gerencsér, L., Gábor Vásárhelyi, Máté Nagy, Tamás Vicsek, & Ádám Miklósi. (2013). Identification of Behaviour in Freely Moving Dogs (Canis familiaris) Using Inertial Sensors. PLoS ONE. 8(10). e77814–e77814. 77 indexed citations
18.
Tarcai, Norbert, Csaba Virágh, Dániel Ábel, et al.. (2011). Patterns, transitions and the role of leaders in the collective dynamics of a simple robotic flock. Journal of Statistical Mechanics Theory and Experiment. 2011(4). P04010–P04010. 23 indexed citations
19.
Nagy, Máté, Zsuzsa Ákos, Dora Biro, & Tamás Vicsek. (2010). Hierarchical group dynamics in pigeon flocks. Nature. 464(7290). 890–893. 758 indexed citations breakdown →
20.
Szabó, Péter, Máté Nagy, & Tamás Vicsek. (2009). Transitions in a self-propelled-particles model with coupling of accelerations. Physical Review E. 79(2). 21908–21908. 35 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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