Maxime Jacquot

257 total papers · 4.7k total citations
75 papers, 3.3k citations indexed

About

Maxime Jacquot is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Biomedical Engineering. According to data from OpenAlex, Maxime Jacquot has authored 75 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Atomic and Molecular Physics, and Optics, 28 papers in Electrical and Electronic Engineering and 22 papers in Biomedical Engineering. Recurrent topics in Maxime Jacquot's work include Neural Networks and Reservoir Computing (19 papers), Photonic and Optical Devices (17 papers) and Advanced Fiber Laser Technologies (15 papers). Maxime Jacquot is often cited by papers focused on Neural Networks and Reservoir Computing (19 papers), Photonic and Optical Devices (17 papers) and Advanced Fiber Laser Technologies (15 papers). Maxime Jacquot collaborates with scholars based in France, Belgium and Spain. Maxime Jacquot's co-authors include Laurent Larger, John M. Dudley, François Courvoisier, Luca Furfaro, Yanne K. Chembo, P.-A. Lacourt, Daniel Brunner, Luc Froehly, M. K. Bhuyan and Romain Martinenghi and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Reviews of Modern Physics.

In The Last Decade

Maxime Jacquot

71 papers receiving 3.1k citations

Author Peers

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

Author Last Decade Papers Cites
Maxime Jacquot 1.6k 1.3k 1.2k 897 530 75 3.3k
Junji Ohtsubo 1.1k 0.7× 523 0.4× 299 0.3× 213 0.2× 233 0.4× 117 2.2k
Yaron Bromberg 996 0.6× 2.3k 1.7× 1.5k 1.3× 720 0.8× 178 0.3× 76 4.3k
Morten Bache 1.0k 0.6× 2.2k 1.6× 627 0.5× 330 0.4× 50 0.1× 81 3.6k
Dana Z. Anderson 1.3k 0.8× 3.3k 2.4× 977 0.8× 184 0.2× 55 0.1× 129 4.5k
H.‐G. Purwins 1.4k 0.9× 748 0.6× 240 0.2× 349 0.4× 121 0.2× 171 4.7k
Greg Kochanski 731 0.5× 1.2k 0.9× 721 0.6× 323 0.4× 293 0.6× 90 3.9k
A. Gatti 642 0.4× 3.3k 2.4× 1.5k 1.3× 485 0.5× 100 0.2× 108 5.0k
Murti V. Salapaka 901 0.6× 1.5k 1.1× 289 0.3× 501 0.6× 63 0.1× 182 3.0k
Jiagui Wu 990 0.6× 484 0.4× 512 0.4× 97 0.1× 119 0.2× 119 1.9k
William T. M. Irvine 416 0.3× 1.9k 1.4× 415 0.4× 910 1.0× 310 0.6× 59 4.4k

Countries citing papers authored by Maxime Jacquot

Since Specialization
Citations

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

Fields of papers citing papers by Maxime Jacquot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maxime Jacquot

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