Kevin Mayeda

2.9k total citations
79 papers, 2.3k citations indexed

About

Kevin Mayeda is a scholar working on Geophysics, Artificial Intelligence and Civil and Structural Engineering. According to data from OpenAlex, Kevin Mayeda has authored 79 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Geophysics, 13 papers in Artificial Intelligence and 7 papers in Civil and Structural Engineering. Recurrent topics in Kevin Mayeda's work include earthquake and tectonic studies (63 papers), Seismic Waves and Analysis (51 papers) and High-pressure geophysics and materials (36 papers). Kevin Mayeda is often cited by papers focused on earthquake and tectonic studies (63 papers), Seismic Waves and Analysis (51 papers) and High-pressure geophysics and materials (36 papers). Kevin Mayeda collaborates with scholars based in United States, Italy and Germany. Kevin Mayeda's co-authors include W. R. Walter, L. Malagnini, Keiiti Aki, S. Koyanagi, Howard J. Patton, Yuehua Zeng, R. Gök, Mitsuyuki Hoshiba, K. Aki and Paola Morasca and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Geophysical Research Letters and Geophysical Journal International.

In The Last Decade

Kevin Mayeda

74 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kevin Mayeda United States 26 2.2k 381 358 120 54 79 2.3k
George L. Choy United States 26 2.0k 0.9× 220 0.6× 254 0.7× 94 0.8× 34 0.6× 51 2.1k
Heidi Houston United States 28 2.7k 1.2× 427 1.1× 141 0.4× 72 0.6× 53 1.0× 65 2.8k
Charles A. Langston United States 24 3.2k 1.5× 180 0.5× 226 0.6× 175 1.5× 34 0.6× 70 3.3k
V. M. Cruz‐Atienza Mexico 23 1.2k 0.5× 184 0.5× 312 0.9× 85 0.7× 47 0.9× 49 1.3k
Reinoud Sleeman Netherlands 9 589 0.3× 393 1.0× 146 0.4× 131 1.1× 40 0.7× 23 705
M. Hellweg United States 18 1.3k 0.6× 544 1.4× 360 1.0× 236 2.0× 22 0.4× 42 1.5k
Hisashi Nakahara Japan 21 1.3k 0.6× 442 1.2× 99 0.3× 253 2.1× 34 0.6× 68 1.4k
Tomomi Okada Japan 33 3.0k 1.4× 408 1.1× 116 0.3× 67 0.6× 37 0.7× 112 3.1k
Masatoshi Miyazawa Japan 17 1.0k 0.5× 264 0.7× 60 0.2× 109 0.9× 37 0.7× 58 1.2k
Elmer Ruigrok Netherlands 17 1.2k 0.6× 275 0.7× 92 0.3× 376 3.1× 55 1.0× 73 1.3k

Countries citing papers authored by Kevin Mayeda

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Mayeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Mayeda

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Mayeda. A scholar is included among the top collaborators of Kevin Mayeda 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 Kevin Mayeda. Kevin Mayeda 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.
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
2.
Mayeda, Kevin, et al.. (2024). Using a 1D Radially Symmetric Coda Envelope Model for Robust Moment Magnitude (Mw) Estimation in Iraq’s Tectonically Diverse Zones. Bulletin of the Seismological Society of America. 115(3). 1331–1343. 3 indexed citations
3.
Gök, R., W. R. Walter, C. Downie, et al.. (2024). Reliable Earthquake Source Parameters Using Distributed Acoustic Sensing Data Derived from Coda Envelopes. Seismological Research Letters. 95(4). 2208–2220. 8 indexed citations
4.
Mayeda, Kevin, et al.. (2024). Coda Envelope Moment Magnitudes and Source Scaling for Southeastern Canada. Bulletin of the Seismological Society of America. 115(3). 1318–1330. 2 indexed citations
5.
Shelly, D. R., Kevin Mayeda, Morgan P. Moschetti, et al.. (2021). A Big Problem for Small Earthquakes: Benchmarking Routine Magnitudes and Conversion Relationships with Coda Envelope-Derived Mw in Southern Kansas and Northern Oklahoma. Bulletin of the Seismological Society of America. 112(1). 210–225. 21 indexed citations
6.
Walter, W. R., et al.. (2017). Earthquake stress via event ratio levels: Application to the 2011 and 2016 Oklahoma seismic sequences. Geophysical Research Letters. 44(7). 3147–3155. 26 indexed citations
7.
Walter, W. R., et al.. (2013). Examining Earthquake Scaling Via Event Ratio Levels. AGU Fall Meeting Abstracts. 2013. 1 indexed citations
8.
9.
Pasyanos, M. E., W. R. Walter, & Kevin Mayeda. (2012). Exploiting Regional Amplitude Envelopes: A Case Study for Earthquakes and Explosions in the Korean Peninsula. Bulletin of the Seismological Society of America. 102(5). 1938–1948. 19 indexed citations
10.
Mayeda, Kevin & L. Malagnini. (2009). Apparent stress and corner frequency variations in the 1999 Taiwan (Chi‐Chi) sequence: Evidence for a step‐wise increase at Mw ∼ 5.5. Geophysical Research Letters. 36(10). 25 indexed citations
11.
Mayeda, Kevin, et al.. (2007). Regional P Coda for Stable Estimates of Body Wave Magnitude: Extending the Ms:mb Discriminant to Smaller Events. AGUFM. 2007. 1 indexed citations
12.
Mayeda, Kevin, L. Malagnini, & W. R. Walter. (2007). A new spectral ratio method using narrow band coda envelopes: Evidence for non‐self‐similarity in the Hector Mine sequence. Geophysical Research Letters. 34(11). 130 indexed citations
13.
Morasca, Paola, Kevin Mayeda, R. Gök, L. Malagnini, & C. Eva. (2005). A break in self‐similarity in the Lunigiana‐Garfagnana region (northern Apennines). Geophysical Research Letters. 32(22). 7 indexed citations
14.
Mayeda, Kevin, R. Gök, A. Hofstetter, & W. R. Walter. (2004). Evidence for Non-Constant Energy/Moment Scaling. AGU Fall Meeting Abstracts. 2004. 1 indexed citations
15.
Mayeda, Kevin, et al.. (2003). Source variables and scaling relations for the 1999 North Anatolian fault zone, Turkey earthquakes. Seismological Research Letters. 74(2). 241. 1 indexed citations
16.
Mayeda, Kevin & W. R. Walter. (2003). Earthquake Apparent Stress Scaling. EGS - AGU - EUG Joint Assembly. 3010. 1 indexed citations
17.
Walter, W. R., Kevin Mayeda, & S Ruppert. (2002). Earthquake Apparent Stress Scaling. AGU Fall Meeting Abstracts. 2002. 1 indexed citations
18.
Mayeda, Kevin, et al.. (2000). Phenomenology Research Using Past Nevada Test Site Explosion and Earthquake Data. University of North Texas Digital Library (University of North Texas). 1 indexed citations
19.
Chael, Eric P., et al.. (1999). Prototyping Regional Discrimination Tools with Matseis. University of North Texas Digital Library (University of North Texas). 118(7). 710–713.
20.
Walter, W. R., Kevin Mayeda, & Howard J. Patton. (1995). Phase and spectral ratio discrimination between NTS earthquakes and explosions. Part I: Empirical observations. Bulletin of the Seismological Society of America. 85(4). 1050–1067. 162 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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