Roberto Miorelli

652 total citations
41 papers, 454 citations indexed

About

Roberto Miorelli is a scholar working on Mechanical Engineering, Mechanics of Materials and Ocean Engineering. According to data from OpenAlex, Roberto Miorelli has authored 41 papers receiving a total of 454 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Mechanical Engineering, 24 papers in Mechanics of Materials and 12 papers in Ocean Engineering. Recurrent topics in Roberto Miorelli's work include Non-Destructive Testing Techniques (32 papers), Ultrasonics and Acoustic Wave Propagation (22 papers) and Geophysical Methods and Applications (12 papers). Roberto Miorelli is often cited by papers focused on Non-Destructive Testing Techniques (32 papers), Ultrasonics and Acoustic Wave Propagation (22 papers) and Geophysical Methods and Applications (12 papers). Roberto Miorelli collaborates with scholars based in France, Greece and Italy. Roberto Miorelli's co-authors include Christophe Reboud, Olivier Mesnil, Pierre Calmon, Dominique Lesselier, Bastien Chapuis, Nicola Anselmi, Marco Salucci, Theodoros Theodoulidis, Andrea Massa and Giacomo Oliveri and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Magnetics.

In The Last Decade

Roberto Miorelli

39 papers receiving 442 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roberto Miorelli France 13 288 282 164 97 67 41 454
Christophe Reboud France 11 207 0.7× 147 0.5× 88 0.5× 36 0.4× 62 0.9× 43 329
Jens Prager Germany 13 228 0.8× 452 1.6× 136 0.8× 236 2.4× 96 1.4× 64 637
Radek Kolman Czechia 12 171 0.6× 191 0.7× 16 0.1× 57 0.6× 44 0.7× 46 438
Yuming Wang China 14 271 0.9× 146 0.5× 44 0.3× 14 0.1× 39 0.6× 51 487
Reza Abedi United States 13 106 0.4× 316 1.1× 21 0.1× 98 1.0× 44 0.7× 64 567
Alexander Velichko United Kingdom 18 656 2.3× 970 3.4× 504 3.1× 272 2.8× 46 0.7× 57 1.0k
Zhiyuan Ma China 13 150 0.5× 123 0.4× 24 0.1× 141 1.5× 36 0.5× 74 568
R.S. Sharpe United Kingdom 8 189 0.7× 290 1.0× 93 0.6× 84 0.9× 37 0.6× 20 506
Steven R. Doctor United States 9 183 0.6× 199 0.7× 77 0.5× 60 0.6× 19 0.3× 65 343
Ruochen Huang United Kingdom 19 681 2.4× 385 1.4× 120 0.7× 33 0.3× 138 2.1× 58 809

Countries citing papers authored by Roberto Miorelli

Since Specialization
Citations

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

Fields of papers citing papers by Roberto Miorelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roberto Miorelli

This figure shows the co-authorship network connecting the top 25 collaborators of Roberto Miorelli. A scholar is included among the top collaborators of Roberto Miorelli 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 Roberto Miorelli. Roberto Miorelli 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.
Miorelli, Roberto, et al.. (2024). A physics-embedded deep-learning framework for efficient multi-fidelity modeling applied to guided wave based structural health monitoring. Ultrasonics. 141. 107325–107325. 10 indexed citations
2.
Gatti, Filippo, et al.. (2024). Generative domain-adapted adversarial auto-encoder model for enhanced ultrasonic imaging applications. NDT & E International. 148. 103234–103234. 5 indexed citations
3.
Liu, Yen‐Chen, et al.. (2024). Global Sensitivity Analysis of Ultrasonic Testing Simulations of Slot-Like Defects With Multifidelity Modeling. Journal of Nondestructive Evaluation Diagnostics and Prognostics of Engineering Systems. 8(1).
4.
Aumeunier, M.-H., et al.. (2023). Infrared measurement synthetic database for inverse thermography model based on deep learning. Fusion Engineering and Design. 192. 113598–113598. 4 indexed citations
5.
6.
Jorge-Badiola, D., Claire Davis, Marco Vannucci, et al.. (2023). How the EU project “Online Microstructure Analytics” advances inline sensing of microstructure during steel manufacturing. SHILAP Revista de lepidopterología. 1(1).
7.
Aumeunier, M.-H., et al.. (2022). Development of inverse methods for infrared thermography in fusion devices. Nuclear Materials and Energy. 33. 101231–101231. 4 indexed citations
8.
Miorelli, Roberto, Anastassios Skarlatos, & Christophe Reboud. (2021). Flaw characterization in conductive media based on pulsed Eddy current measurements: A fast non‐iterative inversion approach. IET Science Measurement & Technology. 15(3). 259–267. 3 indexed citations
9.
Miorelli, Roberto, et al.. (2021). Supervised learning strategy for classification and regression tasks applied to aeronautical structural health monitoring problems. Ultrasonics. 113. 106372–106372. 31 indexed citations
10.
Bai, Long, et al.. (2021). Ultrasonic Defect Characterization Using the Scattering Matrix: A Performance Comparison Study of Bayesian Inversion and Machine Learning Schemas. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 68(10). 3143–3155. 26 indexed citations
11.
Miorelli, Roberto, Christophe Reboud, & Marco Salucci. (2019). Innovative Machine Learning Approaches for Nondestructive Evaluation of Materials. SPIRE - Sciences Po Institutional REpository. 2 indexed citations
12.
Skarlatos, Anastassios, et al.. (2019). A regressor-based hysteresis formulation for the magnetic characterisation of low carbon steels. Physica B Condensed Matter. 581. 411935–411935. 5 indexed citations
13.
Miorelli, Roberto, et al.. (2019). Simulation and processing tools for the design and performance evaluation of FMC-TFM techniques. AIP conference proceedings. 2102. 130010–130010. 1 indexed citations
14.
Miorelli, Roberto, et al.. (2018). Assessing performance of flaw characterization methods through uncertainty propagation. AIP conference proceedings. 1949. 170001–170001. 2 indexed citations
15.
Miorelli, Roberto, et al.. (2017). An efficient adaptive database sampling strategy with applications to eddy current signals. Simulation Modelling Practice and Theory. 80. 75–88. 8 indexed citations
16.
Miorelli, Roberto, et al.. (2016). Solution of the WFNDEC 2015 eddy current benchmark with surface integral equation method. AIP conference proceedings. 1706. 190002–190002. 1 indexed citations
17.
Salucci, Marco, Nicola Anselmi, Giacomo Oliveri, et al.. (2016). Real-Time NDT-NDE Through an Innovative Adaptive Partial Least Squares SVR Inversion Approach. IEEE Transactions on Geoscience and Remote Sensing. 54(11). 6818–6832. 60 indexed citations
18.
Miorelli, Roberto, et al.. (2014). Coupled approach VIM–BEM for efficient modeling of ECT signal due to narrow cracks and volumetric flaws in planar layered media. NDT & E International. 62. 178–183. 12 indexed citations
19.
Miorelli, Roberto, Christophe Reboud, & Theodoros Theodoulidis. (2014). 2013 eddy current benchmark problem: Solution via a coupled integral approach. AIP conference proceedings. 2086–2092. 2 indexed citations
20.
Miorelli, Roberto, Christophe Reboud, Theodoros Theodoulidis, & Dominique Lesselier. (2013). BEM modeling for ECT simulation of complex narrow cracks in multilayered structures. AIP conference proceedings. 441–448. 1 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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