Vladimir Nelyub
- Mechanical Engineering
- General Materials Science top 2%
- Biomedical Engineering
- Materials Chemistry
- Electrical and Electronic Engineering
- Co-authors
- А. С. БородулинВ С ТынченкоAndrei GantimurovIvan MalashinG. V. MalyshevaВ В КукарцевAlexey B. PnevSergei Kurashkin
- Topics
- Machine Learning in Materials Science (7 papers)Injection Molding Process and Properties (6 papers)Computational Drug Discovery Methods (5 papers)
- Cited by
- General Materials ScienceNuclear Energy and EngineeringIndustrial and Manufacturing Engineering
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsInternational Journal of Molecular Sciences
- Partner nations
- Russia
In The Last Decade
Vladimir Nelyub
37 papers receiving 298 citations
Peers
Comparison fields: 5 of 85
- Mechanical Engineering 96
- General Materials Science 51
- Biomedical Engineering 41
- Materials Chemistry 37
- Electrical and Electronic Engineering 35
Countries citing papers authored by Vladimir Nelyub
This map shows the geographic impact of Vladimir Nelyub'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 Vladimir Nelyub with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vladimir Nelyub more than expected).
Fields of papers citing papers by Vladimir Nelyub
This network shows the impact of papers produced by Vladimir Nelyub. 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 Vladimir Nelyub. The network helps show where Vladimir Nelyub may publish in the future.
Co-authorship network of co-authors of Vladimir Nelyub
This figure shows the co-authorship network connecting the top 25 collaborators of Vladimir Nelyub. A scholar is included among the top collaborators of Vladimir Nelyub 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 Vladimir Nelyub. Vladimir Nelyub is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 4 | |
| 11 | 1 | |
| 12 | 16 | |
| 13 | 2 | |
| 14 | 31 | |
| 15 | 3 | |
| 16 | 14 | |
| 17 | 2 | |
| 18 | 10 | |
| 19 | 2 | |
| 20 | 28 |
About Vladimir Nelyub
Vladimir Nelyub is a scholar working on General Materials Science, Industrial and Manufacturing Engineering and Mechanical Engineering, having authored 46 papers that have together received 306 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (7 papers), Injection Molding Process and Properties (6 papers) and Computational Drug Discovery Methods (5 papers). The work is most often cited by research in General Materials Science (51 citations), Nuclear Energy and Engineering (6 citations) and Industrial and Manufacturing Engineering (34 citations). Vladimir Nelyub has collaborated with scholars based in Russia. Frequent co-authors include А. С. Бородулин, В С Тынченко, Andrei Gantimurov, Ivan Malashin, G. V. Malysheva, В В Кукарцев, Alexey B. Pnev, Sergei Kurashkin, Ruslan Sergienko and Yadviga Tynchenko. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and International Journal of Molecular 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.