Alexander Sboev

855 total citations
70 papers, 499 citations indexed

About

Alexander Sboev is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Cognitive Neuroscience. According to data from OpenAlex, Alexander Sboev has authored 70 papers receiving a total of 499 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Artificial Intelligence, 22 papers in Electrical and Electronic Engineering and 19 papers in Cognitive Neuroscience. Recurrent topics in Alexander Sboev's work include Advanced Memory and Neural Computing (22 papers), Neural dynamics and brain function (19 papers) and Topic Modeling (19 papers). Alexander Sboev is often cited by papers focused on Advanced Memory and Neural Computing (22 papers), Neural dynamics and brain function (19 papers) and Topic Modeling (19 papers). Alexander Sboev collaborates with scholars based in Russia, China and Taiwan. Alexander Sboev's co-authors include Roman Rybka, Tatiana Litvinova, Edward V. Generozov, В. А. Демин, Nikolay A. Kudryashov, A. V. Emelyanov, А. В. Ситников, Anton Selivanov, Н.В. Зайцева and S.V. Kleyn and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Nanotechnology.

In The Last Decade

Alexander Sboev

64 papers receiving 470 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexander Sboev Russia 12 213 165 86 84 43 70 499
Elie Bou Assi Canada 11 123 0.6× 43 0.3× 53 0.6× 356 4.2× 64 1.5× 46 708
Munirul M. Haque United States 10 64 0.3× 74 0.4× 47 0.5× 24 0.3× 11 0.3× 26 340
Manuel Sánchez-Montañés Spain 12 85 0.4× 23 0.1× 27 0.3× 46 0.5× 12 0.3× 33 322
Sumit Soman India 11 108 0.5× 64 0.4× 49 0.6× 120 1.4× 31 0.7× 38 349
Nasir Hussain Saudi Arabia 7 78 0.4× 64 0.4× 31 0.4× 255 3.0× 7 0.2× 18 438
Pantelis Angelidis Greece 12 40 0.2× 72 0.4× 30 0.3× 306 3.6× 13 0.3× 64 644
Md. Rashed-Al-Mahfuz Bangladesh 10 185 0.9× 25 0.2× 21 0.2× 200 2.4× 81 1.9× 15 585
Farzana Kulsoom Italy 11 102 0.5× 64 0.4× 10 0.1× 47 0.6× 5 0.1× 25 313
Qing Lyu China 12 222 1.0× 42 0.3× 55 0.6× 38 0.5× 12 0.3× 25 668
E. Grace Mary Kanaga India 8 101 0.5× 42 0.3× 9 0.1× 33 0.4× 6 0.1× 47 307

Countries citing papers authored by Alexander Sboev

Since Specialization
Citations

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

Fields of papers citing papers by Alexander Sboev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexander Sboev

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Sboev. A scholar is included among the top collaborators of Alexander Sboev 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 Alexander Sboev. Alexander Sboev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Rybka, Roman, et al.. (2024). Spiking neural network with local plasticity and sparse connectivity for audio classification. Izvestiya VUZ Applied Nonlinear Dynamics.
3.
Sboev, Alexander, et al.. (2024). Neural Network Modeling of Optical Solitons Described by Generalized Nonlinear Schrödinger Equations. Moscow University Physics Bulletin. 79(S2). S666–S675.
4.
Sboev, Alexander, et al.. (2024). Analysis of neural network methods for obtaining soliton solutions of the nonlinear Schrödinger equation. Chaos Solitons & Fractals. 192. 115943–115943. 3 indexed citations
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6.
Liu, Yuanchao, Jiawei Han, Alexander Sboev, & Ilya Makarov. (2023). GEEF: A neural network model for automatic essay feedback generation by integrating writing skills assessment. Expert Systems with Applications. 245. 123043–123043. 2 indexed citations
7.
Sboev, Alexander, et al.. (2023). A deep learning method based on language models for processing natural language Russian commands in human robot interaction. Open Access Repository (Belgorod State National Research University). 9(1). 1 indexed citations
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Sboev, Alexander, et al.. (2022). On the accuracy of Covid-19 forecasting methods in Russia for two years. Procedia Computer Science. 213. 428–434. 1 indexed citations
11.
Sboev, Alexander, et al.. (2022). Data-driven model for identifying related pharmaceutically-significant entities in clinical texts. AIP conference proceedings. 2425. 340003–340003. 1 indexed citations
12.
Sboev, Alexander, et al.. (2021). Automated system for preventing accidents during well construction. Neftyanoe khozyaystvo - Oil Industry. 72–76. 1 indexed citations
13.
Sboev, Alexander, et al.. (2021). Baseline Accuracies of Forecasting COVID-19 Cases in Russian Regions on a Year in Retrospect Using Basic Statistical and Machine Learning Methods. Procedia Computer Science. 193. 276–284. 1 indexed citations
14.
Зайцева, Н.В., et al.. (2019). Drinking water quality: health risk factors and efficiency of control and surveillance activities by Rospotrebnadzor. SHILAP Revista de lepidopterología. 44–55. 18 indexed citations
15.
Зайцева, Н.В., et al.. (2019). Drinking water quality: health risk factors and efficiency of control and surveillance activities by Rospotrebnadzor. Health Risk Analysis. 44–55. 6 indexed citations
16.
Emelyanov, A. V., K. E. Nikiruy, А. В. Ситников, et al.. (2019). Self-adaptive STDP-based learning of a spiking neuron with nanocomposite memristive weights. Nanotechnology. 31(4). 45201–45201. 68 indexed citations
17.
Litvinova, Tatiana, et al.. (2017). Author Gender Prediction in Russian Social Media Texts.. 105–110. 2 indexed citations
18.
Kudryashov, Nikolay A., Roman Rybka, & Alexander Sboev. (2017). Analytical properties of the perturbed FitzHugh–Nagumo model. Applied Mathematics Letters. 76. 142–147. 24 indexed citations
19.
Sboev, Alexander, et al.. (2016). COMPARATIVE ANALYSIS OF THE CALCULATION MODELS FOR ISCHEMIC HEART DISEASE OVERALL RISK IN RAILROAD WORKERS. Russian Journal of Cardiology. 27–33. 4 indexed citations
20.
Sboev, Alexander, et al.. (2012). Coronary heart disease diagnosis by artificial neural networks including genetic polymorphisms and clinical parameters. Journal of Cardiology. 59(2). 190–194. 83 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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