Sylvain Cussat‐Blanc

862 total citations
45 papers, 385 citations indexed

About

Sylvain Cussat‐Blanc is a scholar working on Artificial Intelligence, Molecular Biology and Mechanical Engineering. According to data from OpenAlex, Sylvain Cussat‐Blanc has authored 45 papers receiving a total of 385 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 18 papers in Molecular Biology and 7 papers in Mechanical Engineering. Recurrent topics in Sylvain Cussat‐Blanc's work include Evolutionary Algorithms and Applications (18 papers), Gene Regulatory Network Analysis (12 papers) and Reinforcement Learning in Robotics (7 papers). Sylvain Cussat‐Blanc is often cited by papers focused on Evolutionary Algorithms and Applications (18 papers), Gene Regulatory Network Analysis (12 papers) and Reinforcement Learning in Robotics (7 papers). Sylvain Cussat‐Blanc collaborates with scholars based in France, United States and United Kingdom. Sylvain Cussat‐Blanc's co-authors include Kyle Harrington, Jordan Pollack, Paul Monsarrat, Hervé Luga, Patricia Balaresque, Delphine Maret, Jean Dumoncel, Norbert Telmon, Évelyne Heyer and Lluís Quintana‐Murci and has published in prestigious journals such as Nature Communications, Bioinformatics and Scientific Reports.

In The Last Decade

Sylvain Cussat‐Blanc

40 papers receiving 372 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sylvain Cussat‐Blanc France 11 108 89 70 49 45 45 385
Thomas Ebner Austria 10 281 2.6× 43 0.5× 73 1.0× 60 1.2× 6 0.1× 21 1.8k
Chi‐Wen Hsieh Taiwan 11 37 0.3× 17 0.2× 14 0.2× 119 2.4× 19 0.4× 57 469
Yifu Ding China 13 117 1.1× 99 1.1× 43 0.6× 1 0.0× 20 0.4× 31 669
Andrea Valsecchi Spain 12 19 0.2× 72 0.8× 29 0.4× 81 1.7× 28 0.6× 28 364
Kart–Leong Lim Singapore 9 100 0.9× 66 0.7× 6 0.1× 16 0.3× 4 0.1× 25 400
Yi Fan China 13 57 0.5× 51 0.6× 64 0.9× 74 1.5× 2 0.0× 54 882
Lay See Khoo Malaysia 7 10 0.1× 25 0.3× 25 0.4× 30 0.6× 134 3.0× 16 344
Duo Peng China 14 218 2.0× 166 1.9× 151 2.2× 15 0.3× 12 0.3× 44 636
Atul Kumar Pandey India 11 32 0.3× 24 0.3× 34 0.5× 7 0.1× 4 0.1× 55 412
Ningning Yang China 15 102 0.9× 42 0.5× 103 1.5× 24 0.5× 3 0.1× 56 677

Countries citing papers authored by Sylvain Cussat‐Blanc

Since Specialization
Citations

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

Fields of papers citing papers by Sylvain Cussat‐Blanc

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sylvain Cussat‐Blanc. 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 Sylvain Cussat‐Blanc. The network helps show where Sylvain Cussat‐Blanc may publish in the future.

Co-authorship network of co-authors of Sylvain Cussat‐Blanc

This figure shows the co-authorship network connecting the top 25 collaborators of Sylvain Cussat‐Blanc. A scholar is included among the top collaborators of Sylvain Cussat‐Blanc 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 Sylvain Cussat‐Blanc. Sylvain Cussat‐Blanc 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.
Luga, Hervé, et al.. (2025). Evolution of Inherently Interpretable Visual Control Policies. Proceedings of the Genetic and Evolutionary Computation Conference. 358–367. 1 indexed citations
2.
Balaresque, Patricia, Sébastien Delmotte, Tatyana Hegay, et al.. (2025). Sex and environment shape cochlear sensitivity in human populations worldwide. Scientific Reports. 15(1). 10475–10475. 1 indexed citations
3.
Banzhaf, Wolfgang, et al.. (2024). Data Sampling via Active Learning in Cartesian Genetic Programming for Biomedical Data. SPIRE - Sciences Po Institutional REpository. 90. 1–8.
4.
Cussat‐Blanc, Sylvain, et al.. (2024). Multimodal Adaptive Graph Evolution. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 499–502. 1 indexed citations
5.
Cussat‐Blanc, Sylvain, et al.. (2024). On Search Trajectory Networks for Graph Genetic Programming. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1681–1685.
6.
Bernard, David, Isabelle Ader, Philippe Kémoun, et al.. (2023). Explainable machine learning framework to predict personalized physiological aging. Aging Cell. 22(8). e13872–e13872. 43 indexed citations
7.
Bernard, David B., Jean Dumoncel, Frédéric Vaysse, et al.. (2022). Machine Learning Analysis of the Anatomical Parameters of the Upper Airway Morphology: A Retrospective Study from Cone-Beam CT Examinations in a French Population. Journal of Clinical Medicine. 12(1). 84–84. 3 indexed citations
8.
Cussat‐Blanc, Sylvain, et al.. (2022). Doctors in Medical Data Sciences: A New Curriculum. International Journal of Environmental Research and Public Health. 20(1). 675–675. 3 indexed citations
9.
Puisségur, Marie-Pierre, Sylvain Cussat‐Blanc, Nathalie Van Acker, et al.. (2022). Ultrarapid lytic granule release from CTLs activates Ca 2+ -dependent synaptic resistance pathways in melanoma cells. Science Advances. 8(7). eabk3234–eabk3234. 15 indexed citations
10.
Franchet, Camille, Radu Tudor Ionescu, Josiane Mothe, et al.. (2022). Finding a Suitable Class Distribution for Building Histological Images Datasets Used in Deep Model Training—The Case of Cancer Detection. Journal of Digital Imaging. 35(5). 1326–1349. 1 indexed citations
11.
Cussat‐Blanc, Sylvain, et al.. (2021). Comparison of different machine learning approaches to predict dental age using Demirjian’s staging approach. International Journal of Legal Medicine. 135(2). 665–675. 51 indexed citations
12.
Müller, Sabina, et al.. (2019). Sequential adjustment of cytotoxic T lymphocyte densities improves efficacy in controlling tumor growth. Scientific Reports. 9(1). 12308–12308. 11 indexed citations
13.
Bernard, David B., et al.. (2019). A checkpoint-oriented cell cycle simulation model. Cell Cycle. 18(8). 795–808. 6 indexed citations
14.
Cussat‐Blanc, Sylvain, et al.. (2019). Speciation under changing environments. HAL (Le Centre pour la Communication Scientifique Directe). 349–356. 1 indexed citations
15.
Balaresque, Patricia, Nicolas Poulet, Sylvain Cussat‐Blanc, et al.. (2015). Y-chromosome descent clusters and male differential reproductive success: young lineage expansions dominate Asian pastoral nomadic populations. European Journal of Human Genetics. 23(10). 1413–1422. 53 indexed citations
16.
Cussat‐Blanc, Sylvain, et al.. (2014). Self-organization of Symbiotic Multicellular Structures. Open Archive Toulouse Archive Ouverte (University of Toulouse). 1 indexed citations
17.
Harrington, Kyle, et al.. (2013). Robot coverage control by evolved neuromodulation. 1. 1–8. 5 indexed citations
18.
Cussat‐Blanc, Sylvain, et al.. (2011). Artificial gene regulatory networks and spatial computation: A case study. HAL (Le Centre pour la Communication Scientifique Directe). 10 indexed citations
19.
Cussat‐Blanc, Sylvain, et al.. (2011). L-systems and artificial chemistry to develop digital organisms. 4. 225–232. 2 indexed citations
20.
Cussat‐Blanc, Sylvain, et al.. (2010). Morphogen Positioning by the Means of a Hydrodynamic Engine.. Artificial Life. 118–125. 2 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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