Alexandre Cury

1.1k total citations
58 papers, 802 citations indexed

About

Alexandre Cury is a scholar working on Civil and Structural Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Alexandre Cury has authored 58 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Civil and Structural Engineering, 9 papers in Mechanical Engineering and 5 papers in Mechanics of Materials. Recurrent topics in Alexandre Cury's work include Structural Health Monitoring Techniques (40 papers), Infrastructure Maintenance and Monitoring (31 papers) and Concrete Corrosion and Durability (25 papers). Alexandre Cury is often cited by papers focused on Structural Health Monitoring Techniques (40 papers), Infrastructure Maintenance and Monitoring (31 papers) and Concrete Corrosion and Durability (25 papers). Alexandre Cury collaborates with scholars based in Brazil, Portugal and France. Alexandre Cury's co-authors include Flávio de Souza Barbosa, Christian Crémona, Christian Crémona, Carlos Magluta, Ney Roitman, Edwin Diday, Diogo Ribeiro, Júlia Castro Mendes, Carmelo Gentile and Rui Calçada and has published in prestigious journals such as SHILAP Revista de lepidopterología, Construction and Building Materials and Expert Systems with Applications.

In The Last Decade

Alexandre Cury

50 papers receiving 785 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexandre Cury Brazil 19 691 171 123 70 40 58 802
Mohsen Azimi Iran 8 744 1.1× 168 1.0× 179 1.5× 72 1.0× 23 0.6× 19 884
Shiyin Wei China 8 698 1.0× 144 0.8× 137 1.1× 93 1.3× 47 1.2× 17 833
S. Farid Ghahari United States 17 784 1.1× 86 0.5× 96 0.8× 108 1.5× 39 1.0× 49 852
Yaozhi Luo China 14 370 0.5× 96 0.6× 105 0.9× 60 0.9× 33 0.8× 46 505
Rolands Kromanis United Kingdom 14 533 0.8× 86 0.5× 83 0.7× 38 0.5× 41 1.0× 31 656
K. Krishnan Nair United States 10 696 1.0× 167 1.0× 238 1.9× 71 1.0× 13 0.3× 13 784
Bartłomiej Błachowski Poland 14 665 1.0× 168 1.0× 200 1.6× 68 1.0× 39 1.0× 42 758
Sutanu Bhowmick United States 9 743 1.1× 111 0.6× 99 0.8× 41 0.6× 32 0.8× 13 849
Norhisham Bakhary Malaysia 17 757 1.1× 162 0.9× 271 2.2× 61 0.9× 71 1.8× 42 923

Countries citing papers authored by Alexandre Cury

Since Specialization
Citations

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

Fields of papers citing papers by Alexandre Cury

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexandre Cury

This figure shows the co-authorship network connecting the top 25 collaborators of Alexandre Cury. A scholar is included among the top collaborators of Alexandre Cury 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 Alexandre Cury. Alexandre Cury 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.
Saporetti, Camila Martins, et al.. (2025). Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification. Signals. 6(1). 9–9.
2.
Moura, Elineudo Pinho de, et al.. (2025). Evaluation of Detrended Fluctuation Analysis applied to audio signals from drum cymbals in different machine learning classification contexts. Engineering Applications of Artificial Intelligence. 152. 110683–110683.
3.
Cury, Alexandre, et al.. (2025). New perspectives on structural health monitoring using unsupervised quantum machine learning. Mechanical Systems and Signal Processing. 229. 112489–112489. 3 indexed citations
4.
Meixedo, Andreia, et al.. (2025). Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using AutoEncoder Models. Applied Sciences. 15(5). 2662–2662.
5.
Silva, Rúben, Diogo Ribeiro, Andreia Meixedo, et al.. (2024). A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders. SHILAP Revista de lepidopterología. 32(4). 421–443. 12 indexed citations
6.
Cury, Alexandre, et al.. (2023). An automated vibration-based structural damage localization strategy using filter-type feature selection. Mechanical Systems and Signal Processing. 190. 110145–110145. 21 indexed citations
7.
Figueiredo, Elói, et al.. (2023). Transfer Learning for Structural Health Monitoring in Bridges That Underwent Retrofitting. Buildings. 13(9). 2323–2323. 8 indexed citations
8.
Barbosa, Flávio de Souza, et al.. (2023). Semi-supervised structural damage assessment via autoregressive models and evolutionary optimization. Structures. 59. 105762–105762. 4 indexed citations
9.
Barbosa, Flávio de Souza, et al.. (2023). Novelty detection on a laboratory benchmark slender structure using an unsupervised deep learning algorithm. Latin American Journal of Solids and Structures. 20(9). 3 indexed citations
10.
Figueiredo, Elói, et al.. (2023). Foundations and applicability of transfer learning for structural health monitoring of bridges. Mechanical Systems and Signal Processing. 204. 110766–110766. 27 indexed citations
11.
Saporetti, Camila Martins, et al.. (2022). Data-driven cymbal bronze alloy identification via evolutionary machine learning with automatic feature selection. Journal of Intelligent Manufacturing. 35(1). 257–273. 6 indexed citations
12.
Cury, Alexandre, et al.. (2021). A fast and efficient feature extraction methodology for structural damage localization based on raw acceleration measurements. Structural Control and Health Monitoring. 28(7). 18 indexed citations
13.
Cury, Alexandre, et al.. (2021). Assessment of low-cost wireless sensors for structural health monitoring applications. SHILAP Revista de lepidopterología. 14(2). 2 indexed citations
14.
Cury, Alexandre, et al.. (2019). Automated real-time damage detection strategy using raw dynamic measurements. Engineering Structures. 196. 109364–109364. 41 indexed citations
15.
Cury, Alexandre, et al.. (2018). Analysis of thermal and damage effects over structural modal parameters. STRUCTURAL ENGINEERING AND MECHANICS. 65(1). 43. 6 indexed citations
16.
Cury, Alexandre, et al.. (2017). DEVELOPMENT OF LOW-COST WIRELESS ACCELEROMETER FOR STRUCTURAL DYNAMIC MONITORING. Americanae (AECID Library).
17.
Cury, Alexandre, Christian Crémona, & Edwin Diday. (2014). A methodology based on symbolic data analysis for structural damage assessment. Base Institutionnelle de Recherche de l'université Paris-Dauphine (BIRD) (University Paris-Dauphine).
18.
Bouteiller, Véronique, et al.. (2012). Non-destructive electrochemical characterizations of reinforced concrete corrosion: basic and symbolic data analysis. Corrosion Reviews. 30(1-2). 47–62. 3 indexed citations
19.
Crémona, Christian, et al.. (2011). Symbolic data analysis and supervised/ non supervised learning algorithms for bridge health monitoring.. 1. 1 indexed citations
20.
Cury, Alexandre & Christian Crémona. (2010). Long term dynamic monitoring of a PSC box girder bridge. Report. 97. 484–485. 4 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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