François Bavaud

84 total papers · 601 total citations
35 papers, 302 citations indexed

About

François Bavaud is a scholar working on Artificial Intelligence, Economics and Econometrics and Statistical and Nonlinear Physics. According to data from OpenAlex, François Bavaud has authored 35 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 7 papers in Economics and Econometrics and 5 papers in Statistical and Nonlinear Physics. Recurrent topics in François Bavaud's work include Spatial and Panel Data Analysis (5 papers), Natural Language Processing Techniques (4 papers) and Sensory Analysis and Statistical Methods (4 papers). François Bavaud is often cited by papers focused on Spatial and Panel Data Analysis (5 papers), Natural Language Processing Techniques (4 papers) and Sensory Analysis and Statistical Methods (4 papers). François Bavaud collaborates with scholars based in Switzerland, United Kingdom and United States. François Bavaud's co-authors include Aris Xanthos, Yves Le Fur, Masoumeh Kordi, Christian Kaiser, Leïla Kebir, Marie Delaplace, Olivier Galland, António Pais Antunes, Jean‐Pierre Müller and Josep Roca Cladera and has published in prestigious journals such as Reviews of Modern Physics, Food Research International and Communications in Mathematical Physics.

In The Last Decade

François Bavaud

29 papers receiving 274 citations

Author Peers

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

Author						Papers	Cites
François Bavaud	116	45	36	31	30	35	302
Hans Nyquist	45 0.4×	18 0.4×	6 0.2×	7 0.2×	31 1.0×	31	365
Pablo Gregori	66 0.6×	89 2.0×	16 0.4×	4 0.1×	36 1.2×	29	355
A. P. J. Abrahamse	71 0.6×	54 1.2×	11 0.3×	2 0.1×	8 0.3×	17	357
Rafael Rigão Souza	74 0.6×	28 0.6×	75 2.1×	7 0.2×	4 0.1×	15	291
Jussi Klemelä	40 0.3×	23 0.5×	8 0.2×	3 0.1×	8 0.3×	28	321
Marco Cirant	59 0.5×	103 2.3×	35 1.0×	5 0.2×	9 0.3×	27	312
Harald Bohman	38 0.3×	61 1.4×	10 0.3×	2 0.1×	4 0.1×	30	287
Rajeev Rajaram	24 0.2×	9 0.2×	61 1.7×	5 0.2×	12 0.4×	38	357
Hongwei Long	93 0.8×	16 0.4×	20 0.6×	3 0.1×	21 0.7×	37	365
Arturo Ramos	112 1.0×	18 0.4×	190 5.3×	17 0.5×	36 1.2×	32	354

Countries citing papers authored by François Bavaud

Since Specialization

Citations

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

Fields of papers citing papers by François Bavaud

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of François Bavaud

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