Ruslan Shevchuk
- Artificial Intelligence
- Information Systems top 10%
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Sociology and Political Science
- Co-authors
- Mikołaj KarpińskiAndriy MelnykMykola DyvakVasyl MartsenyukEmanuele FrontoniAlexandr KuznetsovAndrii ІatsyshynVladlena Benson
- Topics
- Coding theory and cryptography (7 papers)Statistical and Computational Modeling (7 papers)Chaos-based Image/Signal Encryption (6 papers)
- Journals
- IEEE AccessSensorsApplied Sciences
In The Last Decade
Ruslan Shevchuk
35 papers receiving 188 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 86
- Information Systems 68
- Computer Networks and Communications 25
- Computer Vision and Pattern Recognition 25
- Sociology and Political Science 23
Countries citing papers authored by Ruslan Shevchuk
This map shows the geographic impact of Ruslan Shevchuk'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 Ruslan Shevchuk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruslan Shevchuk more than expected).
Fields of papers citing papers by Ruslan Shevchuk
This network shows the impact of papers produced by Ruslan Shevchuk. 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 Ruslan Shevchuk. The network helps show where Ruslan Shevchuk may publish in the future.
Co-authorship network of co-authors of Ruslan Shevchuk
This figure shows the co-authorship network connecting the top 25 collaborators of Ruslan Shevchuk. A scholar is included among the top collaborators of Ruslan Shevchuk 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 Ruslan Shevchuk. Ruslan Shevchuk 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 | 6 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 13 | |
| 12 | 0 | |
| 13 | 16 | |
| 14 | 5 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 10 | |
| 19 | Formalized analysis of the web-site structure | 1 |
| 20 | Analysis of surfaces creation methods in computer graphics tools | 1 |
About Ruslan Shevchuk
Ruslan Shevchuk is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications, having authored 45 papers that have together received 198 indexed citations. Recurring topics across this work include Coding theory and cryptography (7 papers), Statistical and Computational Modeling (7 papers) and Chaos-based Image/Signal Encryption (6 papers). The work is most often cited by research in Nuclear Energy and Engineering (2 citations), Information Systems (68 citations) and Artificial Intelligence (86 citations). Ruslan Shevchuk has collaborated with scholars based in Ukraine, Poland and Italy. Frequent co-authors include Mikołaj Karpiński, Andriy Melnyk, Mykola Dyvak, Vasyl Martsenyuk, Emanuele Frontoni, Alexandr Kuznetsov, Andrii Іatsyshyn, Vladlena Benson and Natalia Porplytsya. Their work appears in journals such as IEEE Access, Sensors and Applied Sciences.
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.