Roman Suvorov

1.3k total citations · 1 hit paper
17 papers, 682 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 682 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 Topic Modeling (2 papers), Web Data Mining and Analysis (2 papers) and Global Trade and Competitiveness (2 papers). Roman Suvorov is often cited by papers focused on Topic Modeling (2 papers), Web Data Mining and Analysis (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 Victor Lempitsky, Elizaveta Logacheva, Arsenii Ashukha, Naejin Kong, Harshith Goka, Aleksandr I. Panov, Konstantin Yakovlev, Bram Adams, Meiyappan Nagappan and Ying Zou 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 655 citations

Hit Papers

1 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Resolution-robust Large Mask Inpainting with Fourier Convolutions

2022 503 citations Roman Suvorov, Elizaveta Logacheva et al. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Roman Suvorov Russia	5	490	107	93	59	45	17	682
Hao Zhao China	15	486 1.0×	143 1.3×	58 0.6×	64 1.1×	80 1.8×	47	768
Jae‐Pil Heo South Korea	12	692 1.4×	179 1.7×	76 0.8×	75 1.3×	42 0.9×	57	825
Jingwen Ye China	12	606 1.2×	259 2.4×	107 1.2×	57 1.0×	36 0.8×	19	856
Shuyang Gu China	8	723 1.5×	156 1.5×	180 1.9×	58 1.0×	106 2.4×	26	984
Hanli Zhao China	16	355 0.7×	190 1.8×	105 1.1×	79 1.3×	59 1.3×	54	646
Wei Xing China	16	543 1.1×	78 0.7×	110 1.2×	70 1.2×	54 1.2×	57	774
Pavel Tokmakov United States	9	364 0.7×	103 1.0×	139 1.5×	19 0.3×	125 2.8×	17	531
Dehui Kong China	13	586 1.2×	269 2.5×	28 0.3×	48 0.8×	71 1.6×	91	732
Simone Milani Italy	19	1.2k 2.4×	101 0.9×	68 0.7×	116 2.0×	92 2.0×	112	1.4k

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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17 of 17 papers shown

Maltseva, D. V., et al.. (2024). Incautious design of shRNAs for stable overexpression of miRNAs could result in generation of undesired isomiRs. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms. 1867(3). 195046–195046. 2 indexed citations

Suvorov, Roman, Elizaveta Logacheva, Arsenii Ashukha, et al.. (2022). Resolution-robust Large Mask Inpainting with Fourier Convolutions. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 3172–3182. 503 indexed citations breakdown →

Соколов, И. А., et al.. (2019). On Creating a National System for Identifying Research and Development Priorities. Scientific and Technical Information Processing. 46(1). 14–19. 1 indexed citations

Suvorov, Roman, et al.. (2018). Mapping the Research Landscape of Agricultural Sciences. Foresight-Russia. 12(1). 69–78. 5 indexed citations

Suvorov, Roman, et al.. (2018). Surface Molecular Markers of Cancer Stem Cells: Computation Analysis of Full-Text Scientific Articles. Bulletin of Experimental Biology and Medicine. 166(1). 135–140. 8 indexed citations

Suvorov, Roman, et al.. (2018). Neural Networks for Food Export Gain Forecasting. 312–317. 4 indexed citations

Suvorov, Roman, et al.. (2018). Fast and Accurate Patent Classification in Search Engines. Journal of Physics Conference Series. 1117. 12004–12004. 3 indexed citations

Panov, Aleksandr I., Konstantin Yakovlev, & Roman Suvorov. (2018). Grid Path Planning with Deep Reinforcement Learning: Preliminary Results. Procedia Computer Science. 123. 347–353. 115 indexed citations

Suvorov, Roman, et al.. (2017). Towards Framework for Discovery of Export Growth Points.. 142–147. 1 indexed citations

10.

Suvorov, Roman, et al.. (2017). A Method for the Identification of Competence Centers Based on the Example of the Artificial Intelligence Domain. Scientific and Technical Information Processing. 44(4). 253–260. 1 indexed citations

11.

Suvorov, Roman, et al.. (2017). An Information Retrieval System for Decision Support: An Arctic-Related Mass Media Case Study. Scientific and Technical Information Processing. 44(5). 329–337.

12.

Kim, Yan, et al.. (2016). A framework for automated meta-analysis: Dendritic cell therapy case study. 160–166. 4 indexed citations

13.

Namazova-Baranova, Leyla S., et al.. (2015). Risk Management of a Patient on the Basis of Remote Health Monitoring: Current Situation and Prospects. Annals of the Russian academy of medical sciences. 70(1). 82–89. 3 indexed citations

14.

Suvorov, Roman, et al.. (2015). Assessment of the Extent of the Necessary Clinical Testing of New Biotechnological Products Based on the Analysis of Scientific Publications and Clinical Trials Reports. 343–348. 1 indexed citations

15.

Suvorov, Roman, et al.. (2015). Establishing the similarity of scientific and technical documents based on thematic significance. Scientific and Technical Information Processing. 42(5). 321–327. 2 indexed citations

16.

Lupatov, А. Yu., et al.. (2015). Assessment of Dendritic Cell Therapy Effectiveness Based on the Feature Extraction from Scientific Publications. 270–276. 3 indexed citations

17.

Suvorov, Roman, Meiyappan Nagappan, Ahmed E. Hassan, Ying Zou, & Bram Adams. (2012). An empirical study of build system migrations in practice: Case studies on KDE and the Linux kernel. PolyPublie (École Polytechnique de Montréal). 160–169. 26 indexed citations

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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