Benoît Hilloulin

1.1k total citations
34 papers, 802 citations indexed

About

Benoît Hilloulin is a scholar working on Civil and Structural Engineering, Environmental Engineering and Mechanics of Materials. According to data from OpenAlex, Benoît Hilloulin has authored 34 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Civil and Structural Engineering, 9 papers in Environmental Engineering and 6 papers in Mechanics of Materials. Recurrent topics in Benoît Hilloulin's work include Concrete and Cement Materials Research (20 papers), Innovative concrete reinforcement materials (14 papers) and Concrete Corrosion and Durability (11 papers). Benoît Hilloulin is often cited by papers focused on Concrete and Cement Materials Research (20 papers), Innovative concrete reinforcement materials (14 papers) and Concrete Corrosion and Durability (11 papers). Benoît Hilloulin collaborates with scholars based in France, Belgium and Vietnam. Benoît Hilloulin's co-authors include Ahmed Loukili, Nele De Belie, Van Quan Tran, Frédéric Grondin, Kim Van Tittelboom, Elke Gruyaert, Odile Abraham, Vincent Tournat, Olivier Durand and Mohammed Matallah and has published in prestigious journals such as Cement and Concrete Research, Construction and Building Materials and Cement and Concrete Composites.

In The Last Decade

Benoît Hilloulin

33 papers receiving 779 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benoît Hilloulin France 14 654 335 116 112 64 34 802
Magdalena Rajczakowska Sweden 13 344 0.5× 131 0.4× 59 0.5× 80 0.7× 82 1.3× 32 460
Sylvia Keßler Germany 14 575 0.9× 127 0.4× 40 0.3× 121 1.1× 219 3.4× 89 667
Alireza Akhavan United States 6 403 0.6× 59 0.2× 87 0.8× 155 1.4× 74 1.2× 8 481
Marta Choińska France 13 614 0.9× 50 0.1× 197 1.7× 162 1.4× 97 1.5× 36 725
Benny Suryanto United Kingdom 19 815 1.2× 45 0.1× 39 0.3× 382 3.4× 72 1.1× 70 898
Pipat Termkhajornkit Japan 12 952 1.5× 181 0.5× 84 0.7× 249 2.2× 233 3.6× 19 1.0k
Fouad Ghomari Algeria 12 438 0.7× 42 0.1× 28 0.2× 198 1.8× 98 1.5× 32 562
Jean‐Louis Gallias France 13 450 0.7× 40 0.1× 39 0.3× 200 1.8× 95 1.5× 44 558
Pejman Azarsa Canada 9 544 0.8× 173 0.5× 9 0.1× 165 1.5× 85 1.3× 12 621

Countries citing papers authored by Benoît Hilloulin

Since Specialization
Citations

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

Fields of papers citing papers by Benoît Hilloulin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benoît Hilloulin

This figure shows the co-authorship network connecting the top 25 collaborators of Benoît Hilloulin. A scholar is included among the top collaborators of Benoît Hilloulin 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 Benoît Hilloulin. Benoît Hilloulin 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.
Roman, Jean, et al.. (2025). Methods for Defining Climate Change Mitigation Strategies at Organisational Level Review and Outlook. Business Strategy and the Environment. 34(3). 2813–2834.
2.
Taffese, Woubishet Zewdu, Benoît Hilloulin, Yury Villagrán Zaccardi, et al.. (2025). Machine learning in concrete durability: challenges and pathways identified by RILEM TC 315-DCS towards enhanced predictive models. Materials and Structures. 58(4). 10 indexed citations
3.
Neupane, Bijay, et al.. (2025). Machine learning algorithms for supporting life cycle assessment studies: An analytical review. Sustainable Production and Consumption. 56. 37–53. 10 indexed citations
4.
Hilloulin, Benoît, et al.. (2025). Combined nanoindentation and SEM imaging for phase quantification and creep prediction of cementitious materials. Materials & Design. 250. 113607–113607. 2 indexed citations
5.
Hilloulin, Benoît, et al.. (2025). Investigation of the creep properties of blended cement pastes using combined nanoindentation and SEM imaging. Construction and Building Materials. 463. 140103–140103. 2 indexed citations
6.
Hilloulin, Benoît, et al.. (2024). Experimental Investigation on the Effects of Mineral Water Composition on the Leaching of Cement-Based Materials. Materials. 17(7). 1548–1548. 2 indexed citations
7.
Hilloulin, Benoît, et al.. (2024). Machine learning-aided prediction of shrinkage in modern concrete: Focus on mix proportions and SCMs. Journal of Building Engineering. 98. 111410–111410. 4 indexed citations
8.
Grondin, Frédéric, et al.. (2023). Creep analysis of cementitious materials in seawater using a poro-chemo-mechanical model. Marine Structures. 90. 103431–103431. 3 indexed citations
9.
Hilloulin, Benoît & Van Quan Tran. (2023). Interpretable machine learning model for autogenous shrinkage prediction of low-carbon cementitious materials. Construction and Building Materials. 396. 132343–132343. 22 indexed citations
10.
Hilloulin, Benoît, et al.. (2023). Coupled effects of simultaneous autogenous self-healing and sustained flexural loading in cementitious materials. Journal of Building Engineering. 79. 107895–107895. 1 indexed citations
11.
Hilloulin, Benoît, et al.. (2023). Interpretable ensemble machine learning for the prediction of the expansion of cementitious materials under external sulfate attack. Journal of Building Engineering. 80. 107951–107951. 13 indexed citations
12.
Hilloulin, Benoît, et al.. (2023). Towards quantifying the effect of pump wave amplitude on cracks in the Nonlinear Coda Wave Interferometry method. Ultrasonics. 132. 106991–106991. 7 indexed citations
13.
Hilloulin, Benoît, et al.. (2022). Open‐source deep learning‐based air‐void detection algorithm for concrete microscopic images. Journal of Microscopy. 286(2). 179–184. 8 indexed citations
14.
Hilloulin, Benoît, et al.. (2022). Modular Deep Learning Segmentation Algorithm for Concrete Microscopic Images. SSRN Electronic Journal. 2 indexed citations
15.
Hilloulin, Benoît, et al.. (2022). ε–greedy automated indentation of cementitious materials for phase mechanical properties determination. Cement and Concrete Composites. 129. 104465–104465. 8 indexed citations
16.
Hilloulin, Benoît, et al.. (2021). Determination of the origin of the strength regain after self-healing of binary and ternary cementitious materials including slag and metakaolin. Journal of Building Engineering. 41. 102739–102739. 25 indexed citations
17.
Mohammadi, Mojtaba, et al.. (2020). Self-Healing Potential and Phase Evolution Characterization of Ternary Cement Blends. Materials. 13(11). 2543–2543. 7 indexed citations
18.
19.
Hilloulin, Benoît, et al.. (2015). Mechanical regains due to self-healing in cementitious materials: Experimental measurements and micro-mechanical model. Cement and Concrete Research. 80. 21–32. 83 indexed citations
20.
Hilloulin, Benoît, et al.. (2013). Design of polymeric capsules for autonomous healing of cracks in cementitious materials. Ghent University Academic Bibliography (Ghent University). 8(8). 660–663. 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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