William H. Savran

563 citations
26 papers · 356 indexed · h-index 12

William H. Savran

24 papers receiving 344 citations

Peers

William H. Savran
Comparison fields: 5 of 37
  • Geophysics 319
  • Artificial Intelligence 200
  • Civil and Structural Engineering 67
  • Information Systems and Management 6
  • Management, Monitoring, Policy and Law 8
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Countries citing papers authored by William H. Savran

Since Specialization
Citations

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

Fields of papers citing papers by William H. Savran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William H. Savran. 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 William H. Savran. The network helps show where William H. Savran may publish in the future.

Co-authorship network

The 25 scholars most cited alongside William H. Savran, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with William H. Savran Line = papers co-authored together William H. Savran links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 20244
4 202310
5 20236
6 20234
7 202219
8 20228
9 202223
10 20212
11 202014
12 202037
13 202020
14
The Collaboratory for the Study of Earthquake Predictability Version 2 (CSEP2): Testing Forecasts that Generate Synthetic Earthquake Catalogs
20191
15 201914
16 201915
17
Verification and Validation of High-Frequency (f max = 5 Hz) Ground Motion Simulations of the 2014 M 5.1 La Habra, California, earthquake
20164
18
Unique Amplification Patterns Generated by Models of Small-scale Crustal Heterogeneities
20141
19 20145
20
Statistics of Velocity Structure in the Los Angeles Area
20131

About William H. Savran

William H. Savran is a scholar working on Geophysics, Artificial Intelligence and Civil and Structural Engineering, having authored 26 papers that have together received 356 indexed citations. Recurring topics across this work include earthquake and tectonic studies (20 papers), Seismology and Earthquake Studies (14 papers), Earthquake Detection and Analysis (13 papers), Seismic Waves and Analysis (6 papers), Seismic Performance and Analysis (5 papers), Geochemistry and Geologic Mapping (4 papers), Structural Health Monitoring Techniques (2 papers) and Seismic Imaging and Inversion Techniques (2 papers). The work is most often cited by research in Geophysics (319 citations), Artificial Intelligence (200 citations) and Civil and Structural Engineering (67 citations). William H. Savran has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include K. B. Olsen, Maximilian J. Werner, David A. Rhoades, Danijel Schorlemmer, Warner Marzocchi, Sebastian Hainzl, Kevin R. Milner, Edward H. Field, T. H. Jordan and Matthew C. Gerstenberger. Their work appears in journals such as SHILAP Revista de lepidopterología, Geophysical Journal International and Bulletin of the Seismological Society of America.

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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