Roman Šenkeřík
- Artificial Intelligence top 1%
- Computational Theory and Mathematics top 2%
- Statistical and Nonlinear Physics top 2%
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering top 5%
- Co-authors
- Michal PluháčekIvan ZelinkaDonald DavendraAdam ViktorinZuzana Komínková OplatkováTomáš KadavýAleš ZamudaSuresh Chandra Satapathy
- Topics
- Metaheuristic Optimization Algorithms Research (66 papers)Evolutionary Algorithms and Applications (54 papers)Neural Networks and Applications (41 papers)
- Cited by
- Artificial IntelligenceStatistical and Nonlinear PhysicsComputational Theory and Mathematics
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
In The Last Decade
Roman Šenkeřík
155 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 121
- Artificial Intelligence 882
- Computational Theory and Mathematics 270
- Statistical and Nonlinear Physics 267
- Computer Vision and Pattern Recognition 231
- Control and Systems Engineering 161
Countries citing papers authored by Roman Šenkeřík
This map shows the geographic impact of Roman Šenkeřík'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 Roman Šenkeřík with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roman Šenkeřík more than expected).
Fields of papers citing papers by Roman Šenkeřík
This network shows the impact of papers produced by Roman Šenkeřík. 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 Roman Šenkeřík. The network helps show where Roman Šenkeřík may publish in the future.
Co-authorship network of co-authors of Roman Šenkeřík
This figure shows the co-authorship network connecting the top 25 collaborators of Roman Šenkeřík. A scholar is included among the top collaborators of Roman Šenkeřík 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 Roman Šenkeřík. Roman Šenkeřík is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 15 | |
| 7 | 22 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 5 | |
| 13 | 5 | |
| 14 | 26 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 8 | |
| 18 | 38 | |
| 19 | 15 | |
| 20 | 20 |
About Roman Šenkeřík
Roman Šenkeřík is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Discrete Mathematics and Combinatorics, having authored 177 papers that have together received 1.5k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (66 papers), Evolutionary Algorithms and Applications (54 papers) and Neural Networks and Applications (41 papers). The work is most often cited by research in Artificial Intelligence (882 citations), Statistical and Nonlinear Physics (267 citations) and Computational Theory and Mathematics (270 citations). Roman Šenkeřík has collaborated with scholars based in Czechia, Vietnam and India. Frequent co-authors include Michal Pluháček, Ivan Zelinka, Donald Davendra, Adam Viktorin, Zuzana Komínková Oplatková, Tomáš Kadavý, Aleš Zamuda, Suresh Chandra Satapathy, Roman Jašek and Radek Šilhavý. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.
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.