N.N. Lepeshkin

24 total papers · 467 total citations
15 papers, 328 citations indexed

About

N.N. Lepeshkin is a scholar working on Atomic and Molecular Physics, and Optics, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, N.N. Lepeshkin has authored 15 papers receiving a total of 328 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Atomic and Molecular Physics, and Optics, 3 papers in Biomedical Engineering and 2 papers in Artificial Intelligence. Recurrent topics in N.N. Lepeshkin's work include Quantum optics and atomic interactions (9 papers), Advanced Fiber Laser Technologies (5 papers) and Cold Atom Physics and Bose-Einstein Condensates (4 papers). N.N. Lepeshkin is often cited by papers focused on Quantum optics and atomic interactions (9 papers), Advanced Fiber Laser Technologies (5 papers) and Cold Atom Physics and Bose-Einstein Condensates (4 papers). N.N. Lepeshkin collaborates with scholars based in United States, Russia and South Korea. N.N. Lepeshkin's co-authors include Robert W. Boyd, Matthew S. Bigelow, Aaron Schweinsberg, Sebastián Jarabo, V. P. Safonov, Vladimir M. Shalaev, R. L. Armstrong, W. Kim, S. G. Rautian and Vadim A. Markel and has published in prestigious journals such as Physical Review Letters, Journal of Physics Condensed Matter and Physica A Statistical Mechanics and its Applications.

In The Last Decade

N.N. Lepeshkin

15 papers receiving 305 citations

Author Peers

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

Author Last Decade Papers Cites
N.N. Lepeshkin 225 108 100 97 30 15 328
Jingjing Hao 264 1.2× 204 1.9× 61 0.6× 111 1.1× 18 0.6× 13 334
Hadi K. Shamkhi 186 0.8× 189 1.8× 85 0.8× 166 1.7× 17 0.6× 15 315
Salvatore Savo 215 1.0× 147 1.4× 66 0.7× 132 1.4× 16 0.5× 10 308
Guang S. He 201 0.9× 129 1.2× 103 1.0× 84 0.9× 63 2.1× 16 333
J. Petschulat 158 0.7× 202 1.9× 83 0.8× 210 2.2× 16 0.5× 17 345
Dongjue Liu 171 0.8× 85 0.8× 172 1.7× 92 0.9× 118 3.9× 13 347
Adriana Canales 268 1.2× 179 1.7× 95 0.9× 67 0.7× 60 2.0× 11 351
Michael Zuerch 203 0.9× 93 0.9× 92 0.9× 102 1.1× 43 1.4× 16 334
Ping Bai 140 0.6× 173 1.6× 97 1.0× 136 1.4× 29 1.0× 13 293
Dorian Bouchet 113 0.5× 165 1.5× 74 0.7× 81 0.8× 22 0.7× 18 264

Countries citing papers authored by N.N. Lepeshkin

Since Specialization
Citations

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

Fields of papers citing papers by N.N. Lepeshkin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of N.N. Lepeshkin

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