M. Guerquin-Kern

11 total papers · 462 total citations
8 papers, 283 citations indexed

About

M. Guerquin-Kern is a scholar working on Radiology, Nuclear Medicine and Imaging, Computational Mechanics and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, M. Guerquin-Kern has authored 8 papers receiving a total of 283 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Computational Mechanics and 3 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in M. Guerquin-Kern's work include Advanced MRI Techniques and Applications (5 papers), Sparse and Compressive Sensing Techniques (4 papers) and Atomic and Subatomic Physics Research (3 papers). M. Guerquin-Kern is often cited by papers focused on Advanced MRI Techniques and Applications (5 papers), Sparse and Compressive Sensing Techniques (4 papers) and Atomic and Subatomic Physics Research (3 papers). M. Guerquin-Kern collaborates with scholars based in Switzerland, United States and France. M. Guerquin-Kern's co-authors include Michaël Unser, Klaas P. Pruessmann, Laure Lejeune, Dimitri Van De Ville, Cédric Vonesch, Antoine Klauser, Michel Kocher and F. Işık Karahanoğlu and has published in prestigious journals such as Magnetic Resonance in Medicine, IEEE Transactions on Medical Imaging and Infoscience (Ecole Polytechnique Fédérale de Lausanne).

In The Last Decade

M. Guerquin-Kern

7 papers receiving 268 citations

Author Peers

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

Author						Papers	Cites
M. Guerquin-Kern	225	132	73	69	36	8	283
Nicolas Chauffert	128 0.6×	78 0.6×	34 0.5×	14 0.2×	18 0.5×	7	157
Alex Sawatzky	184 0.8×	72 0.5×	142 1.9×	75 1.1×	6 0.2×	10	280
G. Desiderá	39 0.2×	102 0.8×	83 1.1×	122 1.8×	85 2.4×	9	285
A. J. Rockmore	205 0.9×	28 0.2×	137 1.9×	58 0.8×	10 0.3×	13	320
Matías Courdurier	246 1.1×	45 0.3×	148 2.0×	34 0.5×	10 0.3×	16	307
François-Xavier Dupé	31 0.1×	100 0.8×	52 0.7×	101 1.5×	7 0.2×	11	222
J D Hale	257 1.1×	16 0.1×	19 0.3×	31 0.4×	69 1.9×	8	318
Juergen H. Massig	21 0.1×	26 0.2×	29 0.4×	72 1.0×	62 1.7×	7	205
Milana Gatarić	22 0.1×	28 0.2×	38 0.5×	42 0.6×	18 0.5×	11	125
Melissa W. Haskell	203 0.9×	6 0.0×	41 0.6×	18 0.3×	53 1.5×	6	285

Countries citing papers authored by M. Guerquin-Kern

Since Specialization

Citations

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

Fields of papers citing papers by M. Guerquin-Kern

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Guerquin-Kern. 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 M. Guerquin-Kern. The network helps show where M. Guerquin-Kern may publish in the future.

Co-authorship network of co-authors of M. Guerquin-Kern

This figure shows the co-authorship network connecting the top 25 collaborators of M. Guerquin-Kern. A scholar is included among the top collaborators of M. Guerquin-Kern 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 M. Guerquin-Kern. M. Guerquin-Kern 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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