Valentin Malykh

119 total papers · 1.1k total citations
38 papers, 246 citations indexed

About

Valentin Malykh is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Valentin Malykh has authored 38 papers receiving a total of 246 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Valentin Malykh's work include Topic Modeling (24 papers), Natural Language Processing Techniques (19 papers) and Advanced Text Analysis Techniques (10 papers). Valentin Malykh is often cited by papers focused on Topic Modeling (24 papers), Natural Language Processing Techniques (19 papers) and Advanced Text Analysis Techniques (10 papers). Valentin Malykh collaborates with scholars based in Russia, Sweden and United States. Valentin Malykh's co-authors include Elena Tutubalina, Sergey Nikolenko, Zulfat Miftahutdinov, Taras Khakhulin, Varvara Logacheva, Ilseyar Alimova, Alexey Sorokin, А. В. Селиверстов, Mikhail Burtsev and Yuri Kuratov and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and Journal of Biomedical Informatics.

In The Last Decade

Valentin Malykh

29 papers receiving 217 citations

Author Peers

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

Author Last Decade Papers Cites
Valentin Malykh 198 62 21 20 17 38 246
Xinhua Zhu 203 1.0× 19 0.3× 14 0.7× 44 2.2× 21 1.2× 33 262
Xingzhi Sun 184 0.9× 72 1.2× 16 0.8× 81 4.0× 21 1.2× 30 304
Svetla Boytcheva 156 0.8× 77 1.2× 20 1.0× 35 1.8× 4 0.2× 46 228
Vincent Claveau 156 0.8× 64 1.0× 53 2.5× 16 0.8× 14 0.8× 40 230
Artem Shelmanov 186 0.9× 22 0.4× 32 1.5× 20 1.0× 14 0.8× 32 247
Yannis Katsis 188 0.9× 55 0.9× 15 0.7× 49 2.5× 18 1.1× 31 294
Suzan Üsküdarlı 123 0.6× 27 0.4× 33 1.6× 32 1.6× 19 1.1× 33 169
Agnieszka Mykowiecka 160 0.8× 78 1.3× 11 0.5× 10 0.5× 9 0.5× 31 205
Conghua Zhou 75 0.4× 23 0.4× 16 0.8× 70 3.5× 7 0.4× 41 234
Lorraine Goeuriot 215 1.1× 88 1.4× 15 0.7× 58 2.9× 17 1.0× 33 269

Countries citing papers authored by Valentin Malykh

Since Specialization
Citations

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

Fields of papers citing papers by Valentin Malykh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Valentin Malykh

This figure shows the co-authorship network connecting the top 25 collaborators of Valentin Malykh. A scholar is included among the top collaborators of Valentin Malykh 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 Valentin Malykh. Valentin Malykh 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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