Milan Kučera

112 total papers · 996 total citations
62 papers, 492 citations indexed

About

Milan Kučera is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications and Applied Mathematics. According to data from OpenAlex, Milan Kučera has authored 62 papers receiving a total of 492 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computational Theory and Mathematics, 15 papers in Computer Networks and Communications and 13 papers in Applied Mathematics. Recurrent topics in Milan Kučera's work include Nonlinear Dynamics and Pattern Formation (15 papers), Advanced Mathematical Modeling in Engineering (12 papers) and Contact Mechanics and Variational Inequalities (12 papers). Milan Kučera is often cited by papers focused on Nonlinear Dynamics and Pattern Formation (15 papers), Advanced Mathematical Modeling in Engineering (12 papers) and Contact Mechanics and Variational Inequalities (12 papers). Milan Kučera collaborates with scholars based in Czechia, Germany and Slovakia. Milan Kučera's co-authors include Pavel Drábek, Jan Eisner, Lucio Boccardo, Martin Väth, Lutz Recke, Daniela Giachetti, Svatopluk Fučík, Jindřich Nečas, Jiřı́ Neustupa and Milan Králik and has published in prestigious journals such as Journal of Mathematical Analysis and Applications, Journal of Differential Equations and Nonlinear Analysis.

In The Last Decade

Milan Kučera

57 papers receiving 410 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Milan Kučera 225 156 134 127 84 62 492
Lutz Recke 261 1.2× 195 1.3× 97 0.7× 17 0.1× 89 1.1× 71 499
Marina Murillo‐Arcila 41 0.2× 210 1.3× 39 0.3× 78 0.6× 73 0.9× 62 504
Ilyasse Aksikas 210 0.9× 45 0.3× 70 0.5× 11 0.1× 442 5.3× 54 536
Abdelbaki Choucha 341 1.5× 150 1.0× 30 0.2× 11 0.1× 376 4.5× 76 478
Cristina Marcelli 101 0.4× 212 1.4× 30 0.2× 184 1.4× 52 0.6× 44 409
J. Solà‐Morales 276 1.2× 252 1.6× 40 0.3× 8 0.1× 225 2.7× 37 493
Steven D. Taliaferro 221 1.0× 394 2.5× 21 0.2× 10 0.1× 47 0.6× 37 504
Wei Mao 20 0.1× 152 1.0× 125 0.9× 81 0.6× 161 1.9× 43 417
Г. В. Демиденко 108 0.5× 340 2.2× 10 0.1× 48 0.4× 106 1.3× 67 509
Nguyen Dinh Cong 27 0.1× 136 0.9× 37 0.3× 30 0.2× 107 1.3× 44 540

Countries citing papers authored by Milan Kučera

Since Specialization
Citations

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

Fields of papers citing papers by Milan Kučera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Milan Kučera

This figure shows the co-authorship network connecting the top 25 collaborators of Milan Kučera. A scholar is included among the top collaborators of Milan Kučera 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 Milan Kučera. Milan Kučera is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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2026