Arnaud Sallaberry

707 total citations
37 papers, 350 citations indexed

About

Arnaud Sallaberry is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Artificial Intelligence. According to data from OpenAlex, Arnaud Sallaberry has authored 37 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 15 papers in Statistical and Nonlinear Physics and 8 papers in Artificial Intelligence. Recurrent topics in Arnaud Sallaberry's work include Data Visualization and Analytics (20 papers), Complex Network Analysis Techniques (15 papers) and Data-Driven Disease Surveillance (5 papers). Arnaud Sallaberry is often cited by papers focused on Data Visualization and Analytics (20 papers), Complex Network Analysis Techniques (15 papers) and Data-Driven Disease Surveillance (5 papers). Arnaud Sallaberry collaborates with scholars based in France, United States and Pakistan. Arnaud Sallaberry's co-authors include Pascal Poncelet, Faraz Zaidi, Guy Mélançon, Dino Ienco, Roberto Interdonato, Andrea Tagarelli, Mathieu Roche, Sandra Bringay, Benjamin Renoust and Maguelonne Teisseire and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Visualization and Computer Graphics and Journal of Biomedical Informatics.

In The Last Decade

Arnaud Sallaberry

36 papers receiving 342 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Arnaud Sallaberry France 12 147 140 106 57 46 37 350
Bruno Pinaud France 8 250 1.7× 103 0.7× 90 0.8× 57 1.0× 34 0.7× 28 358
Aleks Aris United States 7 289 2.0× 122 0.9× 97 0.9× 72 1.3× 30 0.7× 8 385
Christos Giatsidis France 8 84 0.6× 239 1.7× 159 1.5× 41 0.7× 59 1.3× 11 363
Yubao Wu United States 13 119 0.8× 232 1.7× 192 1.8× 62 1.1× 83 1.8× 33 454
Blake Shaw United States 8 117 0.8× 92 0.7× 141 1.3× 46 0.8× 44 1.0× 16 400
Paolo Simonetto United States 9 167 1.1× 105 0.8× 66 0.6× 54 0.9× 13 0.3× 9 245
Christine Largeron France 10 87 0.6× 81 0.6× 140 1.3× 28 0.5× 60 1.3× 33 294
Tarik Crnovrsanin United States 9 218 1.5× 108 0.8× 50 0.5× 68 1.2× 22 0.5× 24 314
Stef van den Elzen Netherlands 9 441 3.0× 156 1.1× 209 2.0× 113 2.0× 33 0.7× 16 550
David Domínguez-Sal Spain 9 93 0.6× 168 1.2× 137 1.3× 36 0.6× 56 1.2× 24 308

Countries citing papers authored by Arnaud Sallaberry

Since Specialization
Citations

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

Fields of papers citing papers by Arnaud Sallaberry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arnaud Sallaberry

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

All Works

20 of 20 papers shown
1.
Sallaberry, Arnaud, et al.. (2025). Task-blind adaptive virtual reality: Is it possible to help users without knowing their assignments?. Virtual Reality. 29(1). 1 indexed citations
2.
Bonnet, Delphine, Sandra Bringay, Arnaud Sallaberry, et al.. (2025). Beyond single drivers: A multi-stressor framework for understanding and managing jellyfish proliferation under concurrent anthropogenic and climate pressures. Ocean & Coastal Management. 270. 107927–107927. 1 indexed citations
3.
Sallaberry, Arnaud, et al.. (2025). How a task-blind adaptive VR system can improve users' task performance: an assisted immersive analytics use case. SPIRE - Sciences Po Institutional REpository. 1–11.
4.
Huchard, Marianne, et al.. (2024). RCAviz: Exploratory search in multi-relational datasets represented using relational concept analysis. International Journal of Approximate Reasoning. 166. 109123–109123. 1 indexed citations
5.
Sallaberry, Arnaud, et al.. (2023). Polygon vector map distortion for increasing the readability of one-to-many flow maps. International Journal of Geographical Information Systems. 37(6). 1288–1314. 2 indexed citations
6.
Azé, Jérôme, et al.. (2022). EBBE-Text: Explaining Neural Networks by Exploring Text Classification Decision Boundaries. IEEE Transactions on Visualization and Computer Graphics. 29(10). 4154–4171. 8 indexed citations
7.
Sallaberry, Arnaud, et al.. (2021). VERTIGo: A Visual Platform for Querying and Exploring Large Multilayer Networks. IEEE Transactions on Visualization and Computer Graphics. 28(3). 1634–1647. 8 indexed citations
8.
Poncelet, Pascal, et al.. (2020). Node Overlap Removal Algorithms: an Extended Comparative Study. Journal of Graph Algorithms and Applications. 24(4). 683–706. 7 indexed citations
9.
Sallaberry, Arnaud, et al.. (2019). EpidVis: A visual web querying tool for animal epidemiology surveillance. Information Visualization. 19(1). 48–64. 4 indexed citations
10.
Sallaberry, Arnaud, et al.. (2018). MultiStream: A Multiresolution Streamgraph Approach to Explore Hierarchical Time Series. IEEE Transactions on Visualization and Computer Graphics. 24(12). 3160–3173. 24 indexed citations
11.
Interdonato, Roberto, Andrea Tagarelli, Dino Ienco, Arnaud Sallaberry, & Pascal Poncelet. (2016). Détection de communautés locales dans des réseaux multicouches. HAL (Le Centre pour la Communication Scientifique Directe). 49 indexed citations
12.
Sallaberry, Arnaud, et al.. (2016). Contact Trees: Network Visualization beyond Nodes and Edges. PLoS ONE. 11(1). e0146368–e0146368. 12 indexed citations
13.
Interdonato, Roberto, Andrea Tagarelli, Dino Ienco, Arnaud Sallaberry, & Pascal Poncelet. (2016). Local community detection in multilayer networks. Data Mining and Knowledge Discovery. 31(5). 1382–1383. 4 indexed citations
14.
Sallaberry, Arnaud, et al.. (2014). Visualizing Time-varying Twitter Data with SentimentClock. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
15.
Jan, Zohaib, et al.. (2013). Tunable and Growing Network Generation Model with Community Structures. arXiv (Cornell University). 1 indexed citations
16.
Auber, David, et al.. (2013). GosperMap: Using a Gosper Curve for Laying Out Hierarchical Data. IEEE Transactions on Visualization and Computer Graphics. 19(11). 1820–1832. 42 indexed citations
17.
Zaidi, Faraz, et al.. (2012). Are All Social Networks Structurally Similar?. 310–314. 15 indexed citations
18.
Brandes, Ulrik, et al.. (2011). Path-based supports for hypergraphs. Journal of Discrete Algorithms. 14. 248–261. 14 indexed citations
19.
Sallaberry, Arnaud, et al.. (2011). Sequential patterns mining and gene sequence visualization to discover novelty from microarray data. Journal of Biomedical Informatics. 44(5). 760–774. 23 indexed citations
20.
Sallaberry, Arnaud, Faraz Zaidi, Christian Pich, & Guy Mélançon. (2010). Interactive visualization and navigation of web search results revealing community structures and bridges. HAL (Le Centre pour la Communication Scientifique Directe). 105–112. 6 indexed citations

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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