A. Maevskiy

49.1k total citations
10 papers, 19 citations indexed

About

A. Maevskiy is a scholar working on Nuclear and High Energy Physics, Radiation and Structural Biology. According to data from OpenAlex, A. Maevskiy has authored 10 papers receiving a total of 19 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Nuclear and High Energy Physics, 4 papers in Radiation and 2 papers in Structural Biology. Recurrent topics in A. Maevskiy's work include Particle physics theoretical and experimental studies (4 papers), Particle Detector Development and Performance (4 papers) and Advanced X-ray Imaging Techniques (3 papers). A. Maevskiy is often cited by papers focused on Particle physics theoretical and experimental studies (4 papers), Particle Detector Development and Performance (4 papers) and Advanced X-ray Imaging Techniques (3 papers). A. Maevskiy collaborates with scholars based in Russia, France and United Kingdom. A. Maevskiy's co-authors include L. Anderlini, I. Snigireva, V. G. Kohn, Maxim V. Grigoriev, Nikolay A. Artemiev, A. Snigirev, Sergey Peredkov, A. S. Boldyrev, N. Kazeev and Д. Деркач and has published in prestigious journals such as SHILAP Revista de lepidopterología, Review of Scientific Instruments and Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment.

In The Last Decade

A. Maevskiy

8 papers receiving 19 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
A. Maevskiy Russia	3	10	5	5	3	3	10	19
A. M. Sirunyan Armenia	3	13 1.3×	3 0.6×	7 1.4×		3 1.0×	5	19
Yongjie Sun China	3	7 0.7×	3 0.6×	9 1.8×	2 0.7×	12 4.0×	7	23
N. Deelen Switzerland	2	3 0.3×	4 0.8×	4 0.8×	4 1.3×	1 0.3×	4	13
A. E. Yakutin Russia	3	9 0.9×	2 0.4×	15 3.0×	2 0.7×	3 1.0×	5	20
Sergey Barsuk France	3	3 0.3×	6 1.2×	9 1.8×	2 0.7×	4 1.3×	4	16
A. Capsoni Italy	2	15 1.5×	3 0.6×	14 2.8×	6 2.0×	5 1.7×	5	25
D. Pugachov Germany	3	8 0.8×	4 0.8×	3 0.6×	2 0.7×	1 0.3×	8	16
T. Rovelli Italy	3	4 0.4×	3 0.6×	6 1.2×	1 0.3×	3 1.0×	7	13
F. Sirghi Italy	3	16 1.6×	1 0.2×	5 1.0×	3 1.0×	3 1.0×	12	21
Anastasia Maria Barbano Switzerland	2	9 0.9×		5 1.0×	6 2.0×	2 0.7×	5	16

Countries citing papers authored by A. Maevskiy

Since Specialization

Citations

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

Fields of papers citing papers by A. Maevskiy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Maevskiy

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

All Works

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10 of 10 papers shown

Maevskiy, A., et al.. (2025). Predicting ionic conductivity in solids from the machine-learned potential energy landscape. Physical Review Research. 7(2). 2 indexed citations

Rodin, Aleksandr, et al.. (2024). Local-time formula for dissipation in solid ionic electrolytes. Physical Review Research. 6(3).

Anderlini, L., M. Barbetti, S. Capelli, et al.. (2024). The LHCb ultra-fast simulation option, Lamarr design and validation. SHILAP Revista de lepidopterología. 295. 3040–3040.

Anderlini, L., M. Barbetti, Д. Деркач, et al.. (2023). Towards Reliable Neural Generative Modeling of Detectors. Journal of Physics Conference Series. 2438(1). 12130–12130. 2 indexed citations

Anderlini, L., M. Barbetti, G. Corti, et al.. (2022). Lamarr: the ultra-fast simulation option for the LHCb experiment. Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022). 233–233. 1 indexed citations

Ratnikov, F., A. Maevskiy, Д. Деркач, et al.. (2022). A full detector description using neural network driven simulation. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1046. 167591–167591. 1 indexed citations

Boldyrev, A. S. & A. Maevskiy. (2015). Simulation of the transition radiation detection conditions in the ATLAS TRT detector filled with argon and krypton gas mixtures. Physics of Atomic Nuclei. 78(13). 1552–1555. 1 indexed citations

Artemiev, Nikolay A., et al.. (2007). Station for investigation with high spatial resolution on Kurchatov SR source. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 575(1-2). 228–230. 3 indexed citations

Snigirev, A., V. G. Kohn, I. Snigireva, et al.. (2006). X-ray parabolic lenses made from glassy carbon by means of laser. Review of Scientific Instruments. 77(6). 3 indexed citations

10.

Snigirev, A., V. G. Kohn, I. Snigireva, et al.. (2005). Planar parabolic X-ray refractive lens made of glassy carbon. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 543(1). 322–325. 6 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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