Joël Chavas

1.3k total citations
15 papers, 265 citations indexed

About

Joël Chavas is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Joël Chavas has authored 15 papers receiving a total of 265 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cellular and Molecular Neuroscience, 4 papers in Molecular Biology and 4 papers in Artificial Intelligence. Recurrent topics in Joël Chavas's work include Photoreceptor and optogenetics research (5 papers), Neuroscience and Neural Engineering (4 papers) and Advanced Memory and Neural Computing (3 papers). Joël Chavas is often cited by papers focused on Photoreceptor and optogenetics research (5 papers), Neuroscience and Neural Engineering (4 papers) and Advanced Memory and Neural Computing (3 papers). Joël Chavas collaborates with scholars based in France, Italy and United Kingdom. Joël Chavas's co-authors include Alain Marty, Thibault Collin, Isabel Llano, E. Pollacco, Nathan Usher, J.-L. Pedroza, E. Delagnes, Β. Blank, P. Baron and L. Nalpas and has published in prestigious journals such as Neuron, Journal of Neuroscience and Molecular Therapy.

In The Last Decade

Joël Chavas

11 papers receiving 259 citations

Peers

Joël Chavas
Comparison fields: 5 of 50
  • Cellular and Molecular Neuroscience 176
  • Cognitive Neuroscience 93
  • Molecular Biology 83
  • Nuclear and High Energy Physics 45
  • Electrical and Electronic Engineering 36
Shelly Lesher United States
Adam Caccavano United States
C. Schroeder Germany
Marco A. Huertas United States
Yasuyuki Abe Japan
Xue Song China
Craig V. Stewart United States
K. W. Bell United Kingdom
Daniel Nunes Portugal
Y. Imai Japan
Shelly Lesher United States View profile →
Citations per field, relative to Joël Chavas
Joël Chavas · 1×
Citations per year, relative to Joël Chavas
Joël Chavas · 1×

Countries citing papers authored by Joël Chavas

Since Specialization
Citations

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

Fields of papers citing papers by Joël Chavas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joël Chavas

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

All Works

15 of 15 papers shown
# Work Indexed citations
1 0
2 3
3 1
4 15
5 1
6 3
7 6
8 1
9 9
10 40
11 0
12 4
13 0
14 42
15 140

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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2026