Antonio Nanni

23.8k total citations · 6 hit papers
510 papers, 15.9k citations indexed

About

Antonio Nanni is a scholar working on Civil and Structural Engineering, Building and Construction and Mechanics of Materials. According to data from OpenAlex, Antonio Nanni has authored 510 papers receiving a total of 15.9k indexed citations (citations by other indexed papers that have themselves been cited), including 457 papers in Civil and Structural Engineering, 390 papers in Building and Construction and 35 papers in Mechanics of Materials. Recurrent topics in Antonio Nanni's work include Structural Behavior of Reinforced Concrete (372 papers), Concrete Corrosion and Durability (249 papers) and Innovative concrete reinforcement materials (237 papers). Antonio Nanni is often cited by papers focused on Structural Behavior of Reinforced Concrete (372 papers), Concrete Corrosion and Durability (249 papers) and Innovative concrete reinforcement materials (237 papers). Antonio Nanni collaborates with scholars based in United States, Italy and Canada. Antonio Nanni's co-authors include Ahmed Mahmoud, Laura De Lorenzis, Fabio Matta, Usama Ebead, Francesco Micelli, Saman Babaeidarabad, Charles E. Bakis, Francisco De Caso, Marco Arduini and Nestore Galati and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Cement and Concrete Research.

In The Last Decade

Antonio Nanni

488 papers receiving 14.6k citations

Hit Papers

Guide for the Design and Construction of Concrete Reinfor... 1998 2026 2007 2016 2005 2017 1998 2018 2021 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Antonio Nanni United States 64 14.9k 12.7k 950 857 778 510 15.9k
A.K.H. Kwan Hong Kong 63 10.3k 0.7× 7.0k 0.5× 327 0.3× 936 1.1× 1.2k 1.6× 285 11.5k
Christopher K.Y. Leung Hong Kong 66 10.5k 0.7× 7.0k 0.5× 150 0.2× 1.4k 1.7× 1.4k 1.8× 310 12.6k
Barzin Mobasher United States 55 5.8k 0.4× 3.5k 0.3× 526 0.6× 1.3k 1.5× 980 1.3× 200 7.0k
Venkatesh Kodur United States 66 12.7k 0.9× 7.2k 0.6× 119 0.1× 640 0.7× 729 0.9× 340 13.8k
Brahim Benmokrane Canada 73 14.8k 1.0× 13.9k 1.1× 79 0.1× 1.4k 1.6× 428 0.6× 433 16.1k
Farhad Aslani Australia 53 7.5k 0.5× 5.3k 0.4× 126 0.1× 313 0.4× 938 1.2× 230 9.3k
Branko Šavija Netherlands 45 4.9k 0.3× 2.7k 0.2× 260 0.3× 775 0.9× 1.1k 1.4× 195 6.7k
Kang Hai Tan Singapore 60 10.7k 0.7× 6.1k 0.5× 140 0.1× 606 0.7× 2.6k 3.4× 409 12.1k
İlker Bekir Topçu Türkiye 44 6.4k 0.4× 4.6k 0.4× 265 0.3× 184 0.2× 766 1.0× 136 7.3k
Joaquim A. O. Barros Portugal 48 8.6k 0.6× 7.8k 0.6× 214 0.2× 564 0.7× 258 0.3× 489 9.1k

Countries citing papers authored by Antonio Nanni

Since Specialization
Citations

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

Fields of papers citing papers by Antonio Nanni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Antonio Nanni

This figure shows the co-authorship network connecting the top 25 collaborators of Antonio Nanni. A scholar is included among the top collaborators of Antonio Nanni 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 Antonio Nanni. Antonio Nanni 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.
Taffese, Woubishet Zewdu, Nima Khodadadi, Yanping Zhu, Seyedali Mirjalili, & Antonio Nanni. (2025). A generative adversarial network enhanced ensemble learning-based prediction model for moment improvement effect of UHPC strengthened damaged RC beams. Case Studies in Construction Materials. 23. e05323–e05323.
3.
Hu, Tianyu, et al.. (2025). Prediction on quasi-static compression deformation modes of circular tubes based on machine learning. International Journal of Mechanical Sciences. 287. 109993–109993. 2 indexed citations
4.
Khodadadi, Nima, et al.. (2025). Explainable Machine Learning Framework with Experimental Validation for Strength Prediction of Magnesium Phosphate Cement. International Journal of Concrete Structures and Materials. 19(1).
6.
Khodadadi, Nima, et al.. (2024). Data-driven PSO-CatBoost machine learning model to predict the compressive strength of CFRP- confined circular concrete specimens. Thin-Walled Structures. 198. 111763–111763. 40 indexed citations
7.
Zhang, Hong, et al.. (2024). Enhancing bond strength prediction at UHPC-NC interface: A data-driven approach with augmentation and explainability. Construction and Building Materials. 451. 138757–138757. 12 indexed citations
9.
Palacios, Juan C., et al.. (2024). Evaluation of Precision Statements for Physio-mechanical Characterization Tests on GFRP Bars. Journal of Testing and Evaluation. 52(4). 2055–2068.
10.
Rahman, Muhammad Kalimur, et al.. (2023). Long-term field monitoring of slabs-on-ground reinforced with GFRP bars. Construction and Building Materials. 404. 133259–133259. 5 indexed citations
11.
Al‐Zahrani, Mesfer M., et al.. (2023). Punching shear capacity of GFRP bar-reinforced concrete slabs-on-ground. Engineering Structures. 289. 116285–116285. 11 indexed citations
12.
Rahman, Muhammad Kalimur, et al.. (2023). Load transfer of small-diameter GFRP and stainless steel doweled-joints in slabs-on-ground. Engineering Structures. 302. 117241–117241. 3 indexed citations
13.
Dolati, Seyed Saman Khedmatgozar, et al.. (2023). Applicability of available NDT methods for damage detection in concrete elements reinforced or strengthened with FRP. Bridge Structures. 19(4). 149–164. 2 indexed citations
14.
Silva, Pedro, et al.. (2023). Flexural strengthening of RC beams using GFRP grid bonded with sprayed polyurea. Engineering Structures. 292. 116516–116516. 7 indexed citations
15.
Mistretta, Fausto, Mario Lucio Puppio, Guido Camata, & Antonio Nanni. (2023). Analytical and experimental shear evaluation of GFRP-reinforced concrete beams. Materials and Structures. 56(10). 6 indexed citations
16.
Accornero, Federico, et al.. (2023). Scale effects in GFRP‐bar reinforced concrete beams. Structural Concrete. 24(2). 2817–2826. 9 indexed citations
17.
Farghaly, Ahmed Sabry, et al.. (2023). Bond behaviour of lap spliced GFRP bars in concrete members: A state-of-the-art review and design recommendations. Construction and Building Materials. 411. 134714–134714. 8 indexed citations
18.
Dolati, Seyed Saman Khedmatgozar, et al.. (2023). Damage and Defects in Fiber-Reinforced Polymer Reinforced and Strengthened Concrete Elements. Journal of Composites for Construction. 27(4). 11 indexed citations
19.
Dolati, Seyed Saman Khedmatgozar, et al.. (2023). Nondestructive Testing Applications for FRP Reinforced or Strengthened Concrete Elements. 3. 217–229. 1 indexed citations
20.
Nanni, Antonio, et al.. (2019). A Seawall Constructed with GFRP Bars as Structural Reinforcing. ACI Concrete International. 41(9). 26–30. 3 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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