В. М. Глушков
- Computational Theory and Mathematics top 2%
- Artificial Intelligence top 5%
- Hardware and Architecture top 5%
- Computer Networks and Communications top 10%
- Molecular Biology
- Co-authors
- A. A. LetichevskiĭYu. V. KapitonovaYuri YatsenkoН. Ф. СтародубB. N. PshenichnyĭN. Z. ShorС. В. БарановA. A. Letichevsky
- Topics
- semigroups and automata theory (7 papers)Logic, programming, and type systems (7 papers)Parallel Computing and Optimization Techniques (7 papers)
- Journals
- Technological Forecasting and Social ChangePhysica D Nonlinear PhenomenaRussian Mathematical Surveys
- Partner nations
- UkraineSpainUnited States
In The Last Decade
В. М. Глушков
42 papers receiving 335 citations
Peers
Comparison fields: 5 of 53
- Computational Theory and Mathematics 295
- Artificial Intelligence 286
- Hardware and Architecture 129
- Computer Networks and Communications 90
- Molecular Biology 75
Countries citing papers authored by В. М. Глушков
This map shows the geographic impact of В. М. Глушков'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 В. М. Глушков with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites В. М. Глушков more than expected).
Fields of papers citing papers by В. М. Глушков
This network shows the impact of papers produced by В. М. Глушков. 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 В. М. Глушков. The network helps show where В. М. Глушков may publish in the future.
Co-authorship network of co-authors of В. М. Глушков
This figure shows the co-authorship network connecting the top 25 collaborators of В. М. Глушков. A scholar is included among the top collaborators of В. М. Глушков 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 В. М. Глушков. В. М. Глушков is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 3 | |
| 3 | The uniqueness of the solutions of one optimization problem | 0 |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 6 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 8 | |
| 11 | 1 | |
| 12 | 0 | |
| 13 | Recursive Machines and Computing Technology. | 29 |
| 14 | 2 | |
| 15 | 12 | |
| 16 | 9 | |
| 17 | 3 | |
| 18 | 4 | |
| 19 | 1 | |
| 20 | 2 |
About В. М. Глушков
В. М. Глушков is a scholar working on Hardware and Architecture, Computational Theory and Mathematics and Industrial and Manufacturing Engineering, having authored 68 papers that have together received 615 indexed citations. Recurring topics across this work include semigroups and automata theory (7 papers), Logic, programming, and type systems (7 papers) and Parallel Computing and Optimization Techniques (7 papers). The work is most often cited by research in Hardware and Architecture (129 citations), Computational Theory and Mathematics (295 citations) and Artificial Intelligence (286 citations). В. М. Глушков has collaborated with scholars based in Ukraine, Spain and United States. Frequent co-authors include A. A. Letichevskiĭ, Yu. V. Kapitonova, Yuri Yatsenko, Н. Ф. Стародуб, B. N. Pshenichnyĭ, N. Z. Shor, С. В. Баранов, A. A. Letichevsky and И. В. Сергиенко. Their work appears in journals such as Technological Forecasting and Social Change, Physica D Nonlinear Phenomena and Russian Mathematical Surveys.
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.