J. Searcy

81.1k total citations
14 papers, 137 citations indexed

About

J. Searcy is a scholar working on Artificial Intelligence, Geophysics and General Health Professions. According to data from OpenAlex, J. Searcy has authored 14 papers receiving a total of 137 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 6 papers in Geophysics and 2 papers in General Health Professions. Recurrent topics in J. Searcy's work include Seismology and Earthquake Studies (6 papers), earthquake and tectonic studies (5 papers) and Earthquake Detection and Analysis (4 papers). J. Searcy is often cited by papers focused on Seismology and Earthquake Studies (6 papers), earthquake and tectonic studies (5 papers) and Earthquake Detection and Analysis (4 papers). J. Searcy collaborates with scholars based in United States, Israel and United Kingdom. J. Searcy's co-authors include Diego Melgar, Amanda M. Thomas, M.-A. Pleier, J. Zhu, Valerie J. Sahakian, D. R. Shelly, Asaf Inbal, Roland Bürgmann, Hannah F. Tavalire and Brian Williams and has published in prestigious journals such as SHILAP Revista de lepidopterología, Geophysical Research Letters and Geophysical Journal International.

In The Last Decade

J. Searcy

10 papers receiving 134 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. Searcy United States 7 77 63 23 7 7 14 137
Roman Yurchak United States 7 30 0.4× 19 0.3× 40 1.7× 1 0.1× 1 0.1× 19 124
Alessandro Sotgiu Italy 3 48 0.6× 94 1.5× 4 0.2× 2 0.3× 11 107
Shyam Nandan Switzerland 9 102 1.3× 159 2.5× 10 1.4× 15 186
N. Agueda Spain 10 62 0.8× 3 0.0× 15 0.7× 2 0.3× 3 0.4× 22 305
Karen Meyer United Kingdom 8 44 0.6× 6 0.1× 7 0.3× 1 0.1× 2 0.3× 20 344
M. Tibbits United States 4 49 0.6× 7 0.1× 3 0.1× 2 0.3× 5 94
D. Pacheco Spain 7 23 0.3× 4 0.1× 15 0.7× 3 0.4× 3 0.4× 9 104
Vikas Joshi India 8 39 0.5× 4 0.1× 128 5.6× 1 0.1× 2 0.3× 24 197
Ariel Almendral Netherlands 6 16 0.2× 77 1.2× 19 2.7× 8 292
Y. Fang United States 5 13 0.2× 3 0.0× 48 2.1× 6 0.9× 22 3.1× 9 99

Countries citing papers authored by J. Searcy

Since Specialization
Citations

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

Fields of papers citing papers by J. Searcy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Searcy

This figure shows the co-authorship network connecting the top 25 collaborators of J. Searcy. A scholar is included among the top collaborators of J. Searcy 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 J. Searcy. J. Searcy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
2.
Thomas, Amanda M., et al.. (2024). Detection of Hidden Low-Frequency Earthquakes in Southern Vancouver Island with Deep Learning. SHILAP Revista de lepidopterología. 2(4).
3.
Tavalire, Hannah F., et al.. (2023). Frontline Data Science: Lessons Learned From a Pandemic. SHILAP Revista de lepidopterología. 5(2). 2 indexed citations
4.
Searcy, J., Camille C. Cioffi, Hannah F. Tavalire, et al.. (2023). Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations. Prevention Science. 24(6). 1249–1260. 4 indexed citations
5.
Thomas, Amanda M., et al.. (2023). Deep learning for denoising High-Rate Global Navigation Satellite System data. SHILAP Revista de lepidopterología. 2(1). 3 indexed citations
6.
Melgar, Diego, et al.. (2023). Real‐Time Fault Tracking and Ground Motion Prediction for Large Earthquakes With HR‐GNSS and Deep Learning. Journal of Geophysical Research Solid Earth. 128(12). 7 indexed citations
7.
Guenther, David A., Kyle Peterson, J. Searcy, & Brian Williams. (2023). How Useful Are Tax Disclosures in Predicting Effective Tax Rates? A Machine Learning Approach. The Accounting Review. 98(5). 297–322. 9 indexed citations
8.
DeGarmo, David S., Stephanie De Anda, Camille C. Cioffi, et al.. (2022). Effectiveness of a COVID-19 Testing Outreach Intervention for Latinx Communities. JAMA Network Open. 5(6). e2216796–e2216796. 14 indexed citations
9.
10.
Melgar, Diego, et al.. (2022). Learning source, path and site effects: CNN-based on-site intensity prediction for earthquake early warning. Geophysical Journal International. 231(3). 2186–2204. 15 indexed citations
11.
Thomas, Amanda M., Asaf Inbal, J. Searcy, D. R. Shelly, & Roland Bürgmann. (2021). Identification of Low‐Frequency Earthquakes on the San Andreas Fault With Deep Learning. Geophysical Research Letters. 48(13). 15 indexed citations
12.
Melgar, Diego, et al.. (2021). Early Warning for Great Earthquakes From Characterization of Crustal Deformation Patterns With Deep Learning. Journal of Geophysical Research Solid Earth. 126(10). 42 indexed citations
13.
Wang, Jinhong, X. Xiao, L. Guan, et al.. (2019). Mass production of a trigger data serializer ASIC for the upgrade of the muon spectrometer at the ATLAS experiment. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 937. 87–92.
14.
Searcy, J., et al.. (2016). Determination of theWWpolarization fractions inpp→W±W±jjusing a deep machine learning technique. Physical review. D. 93(9). 26 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Roman Yurchak Breakdown of academic impact, for papers by Alessandro Sotgiu Breakdown of academic impact, for papers by Shyam Nandan Breakdown of academic impact, for papers by N. Agueda Breakdown of academic impact, for papers by Karen Meyer Breakdown of academic impact, for papers by M. Tibbits Breakdown of academic impact, for papers by D. Pacheco Breakdown of academic impact, for papers by Vikas Joshi Breakdown of academic impact, for papers by Ariel Almendral Breakdown of academic impact, for papers by Y. Fang
Rankless by CCL
2026