Dino Bindi

7.5k total citations
198 papers, 5.7k citations indexed

About

Dino Bindi is a scholar working on Geophysics, Civil and Structural Engineering and Artificial Intelligence. According to data from OpenAlex, Dino Bindi has authored 198 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 178 papers in Geophysics, 97 papers in Civil and Structural Engineering and 54 papers in Artificial Intelligence. Recurrent topics in Dino Bindi's work include Seismic Waves and Analysis (124 papers), earthquake and tectonic studies (100 papers) and Seismic Performance and Analysis (92 papers). Dino Bindi is often cited by papers focused on Seismic Waves and Analysis (124 papers), earthquake and tectonic studies (100 papers) and Seismic Performance and Analysis (92 papers). Dino Bindi collaborates with scholars based in Germany, Italy and France. Dino Bindi's co-authors include Stefano Parolai, Francesca Pacor, Lucia Luzi, Fabrice Cotton, Sreeram Reddy Kotha, Adrien Oth, Matteo Picozzi, Daniele Spallarossa, Rodolfo Puglia and Marco Massa and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Scientific Reports.

In The Last Decade

Dino Bindi

191 papers receiving 5.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dino Bindi Germany 42 4.6k 3.3k 1.0k 352 335 198 5.7k
S. E. Hough United States 39 5.0k 1.1× 2.1k 0.6× 764 0.8× 367 1.0× 220 0.7× 165 5.6k
Stephen Hartzell United States 43 5.5k 1.2× 2.6k 0.8× 751 0.7× 325 0.9× 240 0.7× 113 6.2k
S. K. Singh Mexico 47 6.7k 1.4× 2.1k 0.7× 901 0.9× 204 0.6× 331 1.0× 214 7.3k
Yuehua Zeng United States 34 4.6k 1.0× 1.9k 0.6× 770 0.8× 309 0.9× 150 0.4× 71 5.3k
Stefano Parolai Germany 42 4.7k 1.0× 2.3k 0.7× 976 1.0× 374 1.1× 797 2.4× 216 5.7k
Paul Somerville United States 37 4.3k 0.9× 4.3k 1.3× 409 0.4× 349 1.0× 148 0.4× 128 6.2k
John G. Anderson United States 40 5.1k 1.1× 3.0k 0.9× 579 0.6× 245 0.7× 226 0.7× 181 6.9k
Frank Scherbaum Germany 45 5.9k 1.3× 3.9k 1.2× 865 0.9× 432 1.2× 679 2.0× 161 7.5k
Robert Graves United States 42 6.4k 1.4× 5.8k 1.8× 657 0.6× 446 1.3× 468 1.4× 147 9.3k
Matthias Ohrnberger Germany 31 3.7k 0.8× 950 0.3× 958 0.9× 323 0.9× 869 2.6× 81 4.0k

Countries citing papers authored by Dino Bindi

Since Specialization
Citations

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

Fields of papers citing papers by Dino Bindi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dino Bindi

This figure shows the co-authorship network connecting the top 25 collaborators of Dino Bindi. A scholar is included among the top collaborators of Dino Bindi 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 Dino Bindi. Dino Bindi 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.
Bindi, Dino, Adrien Oth, Stefano Parolai, Matteo Picozzi, & Daniele Spallarossa. (2025). Interevent Variability in Ground-Motion Prediction Models: The Role of the Source Parameter Selection. Bulletin of the Seismological Society of America. 115(6). 2857–2866.
2.
Lanzano, Giovanni, Dino Bindi, Chiara Felicetta, et al.. (2025). ITACAext 2.0: A High-Quality Parametric Table of Strong-to-Weak Motion Recordings for Seismological and Engineering Research in Italy. Seismological Research Letters. 96(5). 3295–3316.
3.
Kwiatek, Grzegorz, Dino Bindi, Dirk Becker, et al.. (2024). Stress Drop Variations of (A)Seismic Fault Segments in the Sea of Marmara Region (Northwestern Türkiye) Supported by Different Methodological Approaches. Bulletin of the Seismological Society of America. 115(3). 1016–1030. 4 indexed citations
4.
Mayeda, Kevin, Dino Bindi, Paola Morasca, et al.. (2024). Source-Scaling Comparison and Validation for Ridgecrest, California: Radiated Energy, Apparent Stress, and Mw Using the Coda Calibration Tool (2.6<Mw<7.1). Bulletin of the Seismological Society of America. 115(3). 890–907. 6 indexed citations
5.
Cochran, E. S., A. Baltay, Shanna Chu, et al.. (2024). SCEC/USGS Community Stress-Drop Validation Study: How Spectral Fitting Approaches Influence Measured Source Parameters. Bulletin of the Seismological Society of America. 115(3). 760–776. 10 indexed citations
6.
Picozzi, Matteo, et al.. (2024). Event-specific ground motion anomalies highlight the preparatory phase of earthquakes during the 2016–2017 Italian seismicity. Communications Earth & Environment. 5(1). 2 indexed citations
7.
Picozzi, Matteo, et al.. (2023). On catching the preparatory phase of damaging earthquakes: an example from central Italy. Scientific Reports. 13(1). 14403–14403. 9 indexed citations
8.
Picozzi, Matteo, et al.. (2022). Detection of Spatial and Temporal Stress Changes During the 2016 Central Italy Seismic Sequence by Monitoring the Evolution of the Energy Index. Journal of Geophysical Research Solid Earth. 127(11). 5 indexed citations
9.
10.
Anderson, John G., Fabrice Cotton, & Dino Bindi. (2021). A ground motion based procedure to identify the earthquakes that are the most relevant for probabilistic seismic hazard analysis. Earthquake Spectra. 37(2). 762–788. 5 indexed citations
11.
Razafindrakoto, Hoby N. T., Fabrice Cotton, Dino Bindi, et al.. (2021). Regional Calibration of Hybrid Ground-Motion Simulations in Moderate Seismicity Areas: Application to the Upper Rhine Graben. Bulletin of the Seismological Society of America. 111(3). 1422–1444. 15 indexed citations
12.
Picozzi, Matteo, Dino Bindi, Gaetano Festa, et al.. (2021). Spatiotemporal Evolution of Microseismicity Seismic Source Properties at the Irpinia Near-Fault Observatory, Southern Italy. Bulletin of the Seismological Society of America. 112(1). 226–242. 15 indexed citations
13.
Bindi, Dino, Hoby N. T. Razafindrakoto, Matteo Picozzi, & Adrien Oth. (2021). Stress Drop Derived from Spectral Analysis Considering the Hypocentral Depth in the Attenuation Model: Application to the Ridgecrest Region, California. Bulletin of the Seismological Society of America. 111(6). 3175–3188. 25 indexed citations
14.
15.
Kotha, Sreeram Reddy, Dino Bindi, & Fabrice Cotton. (2017). From Ergodic to Region‐ and Site‐Specific Probabilistic Seismic Hazard Assessment: Method Development and Application at European and Middle Eastern Sites. Earthquake Spectra. 33(4). 1433–1453. 44 indexed citations
16.
Kotha, Sreeram Reddy, Dino Bindi, & Fabrice Cotton. (2017). Site‐Corrected Magnitude‐ and Region‐Dependent Correlations of Horizontal Peak Spectral Amplitudes. Earthquake Spectra. 33(4). 1415–1432. 22 indexed citations
17.
Luca, Flavia De, G. Ameri, Iunio Iervolino, Francesca Pacor, & Dino Bindi. (2014). Toward validation of simulated accelerograms via prediction equations for nonlinear SDOF response. Bristol Research (University of Bristol). 3 indexed citations
18.
Oth, Adrien & Dino Bindi. (2013). Stress drop variations and their relevance for ground motion prediction: case study of Japan. AGUFM. 2013. 1 indexed citations
19.
Pittore, Massimiliano, Dino Bindi, Marc Wieland, et al.. (2011). Seismic hazard and risk in Central Asia. Publication Database GFZ (GFZ German Research Centre for Geosciences). 1–12. 2 indexed citations
20.
Luzi, Lucia, Fabio Sabetta, F. Mele, et al.. (2009). The italian strong motion database: Design, data input and web distribution. 50.

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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