Luis Tenorio

113 total papers · 5.2k total citations
61 papers, 1.6k citations indexed

About

Luis Tenorio is a scholar working on Artificial Intelligence, Astronomy and Astrophysics and Computational Mechanics. According to data from OpenAlex, Luis Tenorio has authored 61 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 11 papers in Astronomy and Astrophysics and 11 papers in Computational Mechanics. Recurrent topics in Luis Tenorio's work include Sparse and Compressive Sensing Techniques (10 papers), Numerical methods in inverse problems (8 papers) and Seismic Imaging and Inversion Techniques (8 papers). Luis Tenorio is often cited by papers focused on Sparse and Compressive Sensing Techniques (10 papers), Numerical methods in inverse problems (8 papers) and Seismic Imaging and Inversion Techniques (8 papers). Luis Tenorio collaborates with scholars based in United States, Spain and Italy. Luis Tenorio's co-authors include John A. Scales, Eldad Haber, Ping Ma, Charles H. Lineweaver, R. D. van der Hilst, Maarten V. de Hoop, Lior Horesh, P. Keegstra, P. M. Lubin and Sang‐Heon Shim and has published in prestigious journals such as Science, Journal of Geophysical Research Atmospheres and Environmental Science & Technology.

In The Last Decade

Luis Tenorio

59 papers receiving 1.4k citations

Hit Papers

Dipole Anisotropy in the ... 1993 2026 2004 2015 1993 50 100 150 200

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Luis Tenorio 520 475 231 166 138 61 1.6k
William I. Newman 531 1.0× 564 1.2× 100 0.4× 77 0.5× 175 1.3× 99 2.2k
Harold Jeffreys 337 0.6× 486 1.0× 54 0.2× 136 0.8× 144 1.0× 113 1.8k
Agnar Pytte 1.2k 2.4× 658 1.4× 356 1.5× 88 0.5× 23 0.2× 32 2.3k
Yekta Gürsel 1.6k 3.1× 243 0.5× 458 2.0× 414 2.5× 107 0.8× 29 2.2k
Yu. A. Kravtsov 223 0.4× 267 0.6× 165 0.7× 128 0.8× 39 0.3× 151 2.1k
Bradley K. Alpert 162 0.3× 96 0.2× 71 0.3× 64 0.4× 74 0.5× 48 1.9k
А. И. Саичев 227 0.4× 299 0.6× 64 0.3× 63 0.4× 148 1.1× 84 1.7k
Rainer Weiß 1.4k 2.7× 250 0.5× 353 1.5× 500 3.0× 138 1.0× 29 2.3k
Don S. Lemons 675 1.3× 172 0.4× 372 1.6× 31 0.2× 77 0.6× 77 1.7k
J. Heading 588 1.1× 342 0.7× 197 0.9× 168 1.0× 19 0.1× 70 1.7k

Countries citing papers authored by Luis Tenorio

Since Specialization
Citations

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

Fields of papers citing papers by Luis Tenorio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luis Tenorio

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

All Works

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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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