Malú Grave

99 total papers · 412 total citations
14 papers, 90 citations indexed

About

Malú Grave is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics and Computational Mechanics. According to data from OpenAlex, Malú Grave has authored 14 papers receiving a total of 90 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Modeling and Simulation, 4 papers in Statistical and Nonlinear Physics and 4 papers in Computational Mechanics. Recurrent topics in Malú Grave's work include COVID-19 epidemiological studies (4 papers), Model Reduction and Neural Networks (4 papers) and Lattice Boltzmann Simulation Studies (3 papers). Malú Grave is often cited by papers focused on COVID-19 epidemiological studies (4 papers), Model Reduction and Neural Networks (4 papers) and Lattice Boltzmann Simulation Studies (3 papers). Malú Grave collaborates with scholars based in Brazil, Italy and United States. Malú Grave's co-authors include Álvaro L. G. A. Coutinho, Alex Viguerie, Alessandro Reali, Roberto F. S. Andrade, Guillermo Lorenzo, Maria Yuri Ichihara, José Manuel Mendes, Rodrigo Burgos, Viviane Boaventura and Pablo Ivan Pereira Ramos and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, BMC Medical Research Methodology and Journal of Biomechanical Engineering.

In The Last Decade

Malú Grave

13 papers receiving 89 citations

Author Peers

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

Author						Papers	Cites
Malú Grave	31	25	25	15	9	14	90
Adam Ellery	4 0.1×	23 0.9×	38 1.5×	8 0.5×	10 1.1×	18	232
S. Bock	12 0.4×	33 1.3×	3 0.1×	6 0.4×		23	266
D. Blanchard	37 1.2×	7 0.3×	16 0.6×		5 0.6×	13	272
Annette F. Stephansen	210 6.8×	17 0.7×	3 0.1×	25 1.7×		9	254
Talitha Washington	14 0.5×	11 0.4×	74 3.0×	1 0.1×	55 6.1×	14	133
Marta Lewicka	95 3.1×	9 0.4×	18 0.7×	1 0.1×	12 1.3×	28	250
Zhaonan Dong	225 7.3×	16 0.6×	4 0.2×	2 0.1×		17	249
Adriano Cortês	183 5.9×	16 0.6×	7 0.3×	2 0.1×		15	235
T. M. Cherry	29 0.9×	17 0.7×	2 0.1×	3 0.2×		10	74
Martin Neumüller	179 5.8×	11 0.4×	7 0.3×	1 0.1×		11	223

Countries citing papers authored by Malú Grave

Since Specialization

Citations

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

Fields of papers citing papers by Malú Grave

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Malú Grave

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