Roman Suvorov

38 total papers · 1.3k total citations
17 papers, 658 citations indexed

About

Roman Suvorov is a scholar working on Information Systems, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Roman Suvorov has authored 17 papers receiving a total of 658 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Information Systems, 5 papers in Artificial Intelligence and 4 papers in Molecular Biology. Recurrent topics in Roman Suvorov's work include Text and Document Classification Technologies (2 papers), Technology and Human Factors in Education and Health (2 papers) and Global Trade and Competitiveness (2 papers). Roman Suvorov is often cited by papers focused on Text and Document Classification Technologies (2 papers), Technology and Human Factors in Education and Health (2 papers) and Global Trade and Competitiveness (2 papers). Roman Suvorov collaborates with scholars based in Russia, Taiwan and Switzerland. Roman Suvorov's co-authors include Arsenii Ashukha, Harshith Goka, Elizaveta Logacheva, Victor Lempitsky, Naejin Kong, Aleksandr I. Panov, Konstantin Yakovlev, Bram Adams, Ying Zou and Ahmed E. Hassan and has published in prestigious journals such as Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms, Bulletin of Experimental Biology and Medicine and Foresight-Russia.

In The Last Decade

Roman Suvorov

16 papers receiving 632 citations

Hit Papers

Resolution-robust Large M... 2022 2026 2023 2024 2022 100 200 300 400

Author Peers

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

Author Last Decade Papers Cites
Roman Suvorov 468 103 89 56 45 17 658
Zhilong Zhang 262 0.6× 189 1.8× 44 0.5× 45 0.8× 29 0.6× 28 743
Hao Zhao 476 1.0× 142 1.4× 58 0.7× 62 1.1× 78 1.7× 45 740
Eunbyung Park 484 1.0× 183 1.8× 95 1.1× 28 0.5× 80 1.8× 20 642
Linlin Liu 328 0.7× 109 1.1× 66 0.7× 30 0.5× 85 1.9× 22 601
J. Gil 387 0.8× 205 2.0× 50 0.6× 48 0.9× 27 0.6× 20 769
Gengshan Yang 552 1.2× 36 0.3× 84 0.9× 54 1.0× 132 2.9× 17 655
Oliver J. Woodford 558 1.2× 205 2.0× 95 1.1× 49 0.9× 62 1.4× 23 778
Rui Chen 487 1.0× 41 0.4× 42 0.5× 77 1.4× 53 1.2× 30 648
Lorenzo Porzi 431 0.9× 101 1.0× 84 0.9× 42 0.8× 84 1.9× 31 666
Miguel Ángel Bautista 324 0.7× 231 2.2× 37 0.4× 19 0.3× 35 0.8× 17 725

Countries citing papers authored by Roman Suvorov

Since Specialization
Citations

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

Fields of papers citing papers by Roman Suvorov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roman Suvorov

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