Maya de Buhan

29 total papers · 474 total citations
17 papers, 300 citations indexed

About

Maya de Buhan is a scholar working on Mathematical Physics, Biomedical Engineering and Control and Systems Engineering. According to data from OpenAlex, Maya de Buhan has authored 17 papers receiving a total of 300 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Mathematical Physics, 7 papers in Biomedical Engineering and 5 papers in Control and Systems Engineering. Recurrent topics in Maya de Buhan's work include Numerical methods in inverse problems (9 papers), Stability and Controllability of Differential Equations (5 papers) and Microwave Imaging and Scattering Analysis (4 papers). Maya de Buhan is often cited by papers focused on Numerical methods in inverse problems (9 papers), Stability and Controllability of Differential Equations (5 papers) and Microwave Imaging and Scattering Analysis (4 papers). Maya de Buhan collaborates with scholars based in France, Chile and Switzerland. Maya de Buhan's co-authors include Sylvain Ervedoza, Lucie Baudouin, Marion Darbas, Axel Osses, Frédéric Hecht, Victorita Dolean, Francesca Rapetti, Serguei Semenov, Frédéric Nataf and Christian Pichot and has published in prestigious journals such as International Journal for Numerical Methods in Engineering, International Journal of Solids and Structures and Mechanical Systems and Signal Processing.

In The Last Decade

Maya de Buhan

15 papers receiving 287 citations

Author Peers

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

Author Last Decade Papers Cites
Maya de Buhan 144 137 80 70 61 17 300
Michele Di Cristo 97 0.7× 277 2.0× 154 1.9× 131 1.9× 39 0.6× 28 306
Eva Sincich 61 0.4× 193 1.4× 92 1.1× 87 1.2× 24 0.4× 27 244
Erkki Heikkola 62 0.4× 28 0.2× 58 0.7× 110 1.6× 25 0.4× 18 314
Dominique Habault 178 1.2× 27 0.2× 36 0.5× 79 1.1× 37 0.6× 25 292
Kazumi Tanuma 91 0.6× 102 0.7× 76 0.9× 240 3.4× 5 0.1× 30 332
Emilia Blåsten 137 1.0× 181 1.3× 66 0.8× 75 1.1× 5 0.1× 21 276
Toomas Raus 77 0.5× 212 1.5× 14 0.2× 31 0.4× 13 0.2× 21 287
Kiriakie Kiriaki 143 1.0× 197 1.4× 35 0.4× 193 2.8× 4 0.1× 18 288
Wenjia Jing 107 0.7× 97 0.7× 78 1.0× 106 1.5× 2 0.0× 23 276
Élie Bretin 74 0.5× 61 0.4× 67 0.8× 82 1.2× 3 0.0× 30 333

Countries citing papers authored by Maya de Buhan

Since Specialization
Citations

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

Fields of papers citing papers by Maya de Buhan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maya de Buhan. 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 Maya de Buhan. The network helps show where Maya de Buhan may publish in the future.

Co-authorship network of co-authors of Maya de Buhan

This figure shows the co-authorship network connecting the top 25 collaborators of Maya de Buhan. A scholar is included among the top collaborators of Maya de Buhan 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 Maya de Buhan. Maya de Buhan 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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