I. Altsybeev

37.6k total citations
11 papers, 24 citations indexed

About

I. Altsybeev is a scholar working on Nuclear and High Energy Physics, Aerospace Engineering and Environmental Engineering. According to data from OpenAlex, I. Altsybeev has authored 11 papers receiving a total of 24 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Nuclear and High Energy Physics, 3 papers in Aerospace Engineering and 1 paper in Environmental Engineering. Recurrent topics in I. Altsybeev's work include High-Energy Particle Collisions Research (11 papers), Particle physics theoretical and experimental studies (9 papers) and Quantum Chromodynamics and Particle Interactions (6 papers). I. Altsybeev is often cited by papers focused on High-Energy Particle Collisions Research (11 papers), Particle physics theoretical and experimental studies (9 papers) and Quantum Chromodynamics and Particle Interactions (6 papers). I. Altsybeev collaborates with scholars based in Russia, France and Switzerland. I. Altsybeev's co-authors include Г. Феофилов, O. Kochebina, V. Zherebchevskii, Corrado Gargiulo, E. Laudi, D. Nesterov, T. Lazareva, V. Kovalenko, A. Francescon and Tapan K. Nayak and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Instrumentation and Journal of Physics Conference Series.

In The Last Decade

I. Altsybeev

10 papers receiving 24 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
I. Altsybeev Russia	3	21	4	3	3	1	11	24
J. Molina Rodriguez Colombia	3	21 1.0×	4 1.0×	2 0.7×			6	23
M.B. Golubeva Russia	4	20 1.0×	6 1.5×	1 0.3×	3 1.0×		8	25
V. Gyurjyan United States	3	16 0.8×	5 1.3×		3 1.0×		11	20
P. Sapienza Italy	2	12 0.6×	4 1.0×	2 0.7×	3 1.0×	1 1.0×	3	12
M. Erhard Germany	3	15 0.7×	6 1.5×		4 1.3×		5	19
D. Nesterov Russia	3	11 0.5×	4 1.0×	3 1.0×		1 1.0×	5	15
Alex Tapia Colombia	3	16 0.8×	4 1.0×	3 1.0×	1 0.3×	1 1.0×	9	20
K. Yoshinaga Japan	2	10 0.5×	4 1.0×	1 0.3×	3 1.0×		3	11
S. Choudhury India	4	30 1.4×	3 0.8×		6 2.0×	1 1.0×	14	31
H. Okawa China	3	22 1.0×	8 2.0×		2 0.7×		6	23

Countries citing papers authored by I. Altsybeev

Since Specialization

Citations

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

Fields of papers citing papers by I. Altsybeev

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of I. Altsybeev

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

All Works

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11 of 11 papers shown

Altsybeev, I., et al.. (2020). Reconstruction of moments of particle distributions with Identity Method at MPD. Journal of Physics Conference Series. 1690(1). 12124–12124.

Altsybeev, I., Evgeny Andronov, & Д. С. Прохорова. (2020). Machine learning techniques for optimisation of track selection criteria. Journal of Physics Conference Series. 1690(1). 12119–12119. 1 indexed citations

Altsybeev, I.. (2020). Application of Principal Component Analysis to Establish a Proper Basis for Flow Studies in Heavy-Ion Collisions. Physics of Particles and Nuclei. 51(3). 314–318. 2 indexed citations

Altsybeev, I.. (2020). On feasibility of azimuthal flow studies with Principal Component Analysis. Journal of Physics Conference Series. 1602(1). 12004–12004. 1 indexed citations

Zherebchevskii, V., I. Altsybeev, Г. Феофилов, et al.. (2018). Experimental investigation of new ultra-lightweight support and cooling structures for the new Inner Tracking System of the ALICE Detector. Journal of Instrumentation. 13(8). T08003–T08003. 8 indexed citations

Altsybeev, I.. (2018). Forward–backward Correlations Between Mean Transverse Momenta in Pb–Pb Collisions with ALICE. KnE Energy. 3(1). 304–304. 2 indexed citations

Altsybeev, I. & V. Kovalenko. (2017). Classifiers for centrality determination in proton-nucleus and nucleus-nucleus collisions. Springer Link (Chiba Institute of Technology). 1 indexed citations

Altsybeev, I., Г. Феофилов, & O. Kochebina. (2016). Constraints on the percolation model from anomalous centrality evolution of two-particle correlations in Au-Au collisions at sNN=62 and 200 GeV. AIP conference proceedings. 1701. 60011–60011. 3 indexed citations

Altsybeev, I. & Г. Феофилов. (2016). Azimuthal flows in hadron collisions from quark-gluon string repulsion. SHILAP Revista de lepidopterología. 125. 4011–4011. 2 indexed citations

10.

Altsybeev, I., et al.. (2015). Constraints on string percolation model from anomalous centrality evolution data in Au-Au collisions at sqrt(s_ NN) = 62 and 200 GeV. 67–67. 2 indexed citations

11.

Altsybeev, I., et al.. (2013). Forward-backward multiplicity correlations in pp collisions in ALICE at 0.9, 2.76 and 7 TeV. CERN Bulletin. 75–75. 2 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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