Ivan Maliyov

468 total citations · 1 hit paper
12 papers, 336 citations indexed

About

Ivan Maliyov is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Materials Chemistry. According to data from OpenAlex, Ivan Maliyov has authored 12 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Atomic and Molecular Physics, and Optics, 6 papers in Electrical and Electronic Engineering and 5 papers in Materials Chemistry. Recurrent topics in Ivan Maliyov's work include Machine Learning in Materials Science (4 papers), Semiconductor materials and devices (4 papers) and Molecular Junctions and Nanostructures (3 papers). Ivan Maliyov is often cited by papers focused on Machine Learning in Materials Science (4 papers), Semiconductor materials and devices (4 papers) and Molecular Junctions and Nanostructures (3 papers). Ivan Maliyov collaborates with scholars based in United States, France and India. Ivan Maliyov's co-authors include Marco Bernardi, Jinsoo Park, I-Te Lu, Jin-Jian Zhou, Xiao Tong, Fabien Bruneval, Jean-Paul Crocombette, Paavo K.J. Kinnunen, Valeriya Trusova and Hiroyuki Saito and has published in prestigious journals such as Journal of Chemical Theory and Computation, Computer Physics Communications and Physical review. B..

In The Last Decade

Ivan Maliyov

10 papers receiving 333 citations

Hit Papers

Perturbo: A software pack... 2021 2026 2022 2024 2021 50 100 150

Author Peers

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

Author Last Decade Papers Cites
Ivan Maliyov 173 145 114 29 23 12 336
Carola Meyer 306 1.8× 203 1.4× 118 1.0× 49 1.7× 19 0.8× 47 478
Thierry Dubroca 234 1.4× 95 0.7× 47 0.4× 30 1.0× 11 0.5× 30 367
Diana Serrano 333 1.9× 257 1.8× 223 2.0× 56 1.9× 16 0.7× 42 549
Ana R. N. Bastos 267 1.5× 115 0.8× 244 2.1× 14 0.5× 28 1.2× 20 439
Christopher Arntsen 89 0.5× 159 1.1× 115 1.0× 40 1.4× 23 1.0× 13 294
Tsuneyasu Okabe 192 1.1× 82 0.6× 28 0.2× 19 0.7× 130 5.7× 15 343
Mykyta Onizhuk 139 0.8× 129 0.9× 107 0.9× 27 0.9× 6 0.3× 22 259
Aritz Leonardo 184 1.1× 222 1.5× 69 0.6× 66 2.3× 15 0.7× 34 372

Countries citing papers authored by Ivan Maliyov

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Maliyov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Maliyov

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

All Works

12 of 12 papers shown
1.
Chen, Hsiao‐Yi, Ivan Maliyov, Jin-Jian Zhou, et al.. (2025). Magnon-phonon interactions from first principles. Physical review. B.. 112(18). 2 indexed citations
2.
Maliyov, Ivan, et al.. (2025). Exploring parameter dependence of atomic minima with implicit differentiation. npj Computational Materials. 11(1). 3 indexed citations
3.
Pérez, Danny, et al.. (2025). Uncertainty quantification for misspecified machine learned interatomic potentials. npj Computational Materials. 11(1).
5.
Maliyov, Ivan, et al.. (2024). Dynamic mode decomposition of nonequilibrium electron-phonon dynamics: accelerating the first-principles real-time Boltzmann equation. npj Computational Materials. 10(1). 6 indexed citations
6.
Zhou, Jin-Jian, Jinsoo Park, I-Te Lu, et al.. (2021). Perturbo: A software package for ab initio electron–phonon interactions, charge transport and ultrafast dynamics. Computer Physics Communications. 264. 107970–107970. 186 indexed citations breakdown →
7.
Maliyov, Ivan, Jinsoo Park, & Marco Bernardi. (2021). Ab initio electron dynamics in high electric fields: Accurate prediction of velocity-field curves. Physical review. B.. 104(10). 14 indexed citations
8.
Bruneval, Fabien, et al.. (2020). Extrapolating Unconverged GW Energies up to the Complete Basis Set Limit with Linear Regression. Journal of Chemical Theory and Computation. 16(7). 4399–4407. 17 indexed citations
9.
Maliyov, Ivan, Jean-Paul Crocombette, & Fabien Bruneval. (2020). Quantitative electronic stopping power from localized basis set. Physical review. B.. 101(3). 11 indexed citations
10.
Li, Dongzhe, et al.. (2019). Symmetry aspects of spin filtering in molecular junctions: Hybridization and quantum interference effects. Physical review. B.. 99(11). 31 indexed citations
11.
Maliyov, Ivan, Jean-Paul Crocombette, & Fabien Bruneval. (2018). Electronic stopping power from time-dependent density-functional theory in Gaussian basis. The European Physical Journal B. 91(8). 24 indexed citations
12.
Girych, Mykhailo, Galyna Gorbenko, Ivan Maliyov, et al.. (2016). Combined thioflavin T–Congo red fluorescence assay for amyloid fibril detection. Methods and Applications in Fluorescence. 4(3). 34010–34010. 42 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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