Aurélien Mayoue

434 total citations
10 papers, 151 citations indexed

About

Aurélien Mayoue is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Aurélien Mayoue has authored 10 papers receiving a total of 151 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 2 papers in Molecular Biology and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Aurélien Mayoue's work include Privacy-Preserving Technologies in Data (5 papers), Cryptography and Data Security (3 papers) and Internet Traffic Analysis and Secure E-voting (2 papers). Aurélien Mayoue is often cited by papers focused on Privacy-Preserving Technologies in Data (5 papers), Cryptography and Data Security (3 papers) and Internet Traffic Analysis and Secure E-voting (2 papers). Aurélien Mayoue collaborates with scholars based in France, Lebanon and United Kingdom. Aurélien Mayoue's co-authors include Cédric Gouy‐Pailler, Renaud Sirdey, Quentin Barthélemy, David Mercier, Jérôme Mars, Nesma Houmani, Marcos Faúndez-Zanuy, Sonia Garcia-Salicetti, Daigo Muramatsu and Julián Fiérrez and has published in prestigious journals such as IEEE Transactions on Signal Processing, Pattern Recognition and HAL (Le Centre pour la Communication Scientifique Directe).

In The Last Decade

Aurélien Mayoue

9 papers receiving 148 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aurélien Mayoue France 5 73 71 47 44 16 10 151
Sergios Petridis Greece 9 67 0.9× 66 0.9× 45 1.0× 15 0.3× 4 0.3× 18 156
Feng Cheng China 8 136 1.9× 52 0.7× 92 2.0× 11 0.3× 4 0.3× 15 218
Pouya Samangouei United States 4 65 0.9× 15 0.2× 60 1.3× 43 1.0× 34 2.1× 5 129
Lorène Allano Germany 7 98 1.3× 25 0.4× 111 2.4× 70 1.6× 2 0.1× 8 158
Laurent El Shafey Switzerland 7 110 1.5× 96 1.4× 159 3.4× 31 0.7× 3 0.2× 21 233
B. Duc Switzerland 5 193 2.6× 28 0.4× 123 2.6× 33 0.8× 3 0.2× 9 244
Hatef Otroshi Shahreza Switzerland 10 203 2.8× 49 0.7× 153 3.3× 58 1.3× 4 0.3× 45 270
Sai Rajeswar India 5 75 1.0× 80 1.1× 15 0.3× 10 0.2× 4 0.3× 10 150
Shant Navasardyan United States 6 201 2.8× 28 0.4× 24 0.5× 5 0.1× 10 0.6× 20 232
Zhourong Chen Hong Kong 7 82 1.1× 87 1.2× 18 0.4× 31 0.7× 2 0.1× 9 164

Countries citing papers authored by Aurélien Mayoue

Since Specialization
Citations

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

Fields of papers citing papers by Aurélien Mayoue

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aurélien Mayoue

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

All Works

10 of 10 papers shown
1.
Mayoue, Aurélien, et al.. (2024). Fantastyc: Blockchain-Based Federated Learning Made Secure and Practical. SPIRE - Sciences Po Institutional REpository. 260–270. 1 indexed citations
2.
3.
Mayoue, Aurélien, et al.. (2024). Federated Dataset Dictionary Learning for Multi-Source Domain Adaptation. SPIRE - Sciences Po Institutional REpository. 5610–5614. 2 indexed citations
4.
Mayoue, Aurélien, et al.. (2023). FUBA: Federated Uncovering of Backdoor Attacks for Heterogeneous Data. SPIRE - Sciences Po Institutional REpository. 33. 55–63. 1 indexed citations
5.
Mayoue, Aurélien, et al.. (2022). Federated learning with incremental clustering for heterogeneous data. 2022 International Joint Conference on Neural Networks (IJCNN). 1–8. 4 indexed citations
6.
Mayoue, Aurélien, et al.. (2021). A Secure Federated Learning framework using Homomorphic Encryption and Verifiable Computing. SPIRE - Sciences Po Institutional REpository. 1–8. 45 indexed citations
7.
Mayoue, Aurélien, et al.. (2013). Recursive Least Squares algorithm dedicated to early recognition of explosive compounds thanks to multi-technology sensors. HAL (Le Centre pour la Communication Scientifique Directe). 8761–8765. 1 indexed citations
8.
Barthélemy, Quentin, et al.. (2012). Shift & 2D Rotation Invariant Sparse Coding for Multivariate Signals. IEEE Transactions on Signal Processing. 60(4). 1597–1611. 31 indexed citations
9.
Houmani, Nesma, Aurélien Mayoue, Sonia Garcia-Salicetti, et al.. (2011). BioSecure signature evaluation campaign (BSEC'2009): Evaluating online signature algorithms depending on the quality of signatures. Pattern Recognition. 45(3). 993–1003. 59 indexed citations
10.
Fauve, Benoît, Hervé Bredin, Aurélien Mayoue, et al.. (2008). Some Results from the Biosecure Talking Face Evaluation Campaign. HAL (Le Centre pour la Communication Scientifique Directe). 1. 4137–4140. 7 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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2026