M. A. Pérez‐Flores

704 total citations
44 papers, 535 citations indexed

About

M. A. Pérez‐Flores is a scholar working on Geophysics, Ocean Engineering and Artificial Intelligence. According to data from OpenAlex, M. A. Pérez‐Flores has authored 44 papers receiving a total of 535 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Geophysics, 24 papers in Ocean Engineering and 6 papers in Artificial Intelligence. Recurrent topics in M. A. Pérez‐Flores's work include Geophysical and Geoelectrical Methods (33 papers), Geophysical Methods and Applications (20 papers) and Seismic Waves and Analysis (12 papers). M. A. Pérez‐Flores is often cited by papers focused on Geophysical and Geoelectrical Methods (33 papers), Geophysical Methods and Applications (20 papers) and Seismic Waves and Analysis (12 papers). M. A. Pérez‐Flores collaborates with scholars based in Mexico, Germany and United Kingdom. M. A. Pérez‐Flores's co-authors include Enrique Gómez‐Treviño, Luis A. Gallardo, Max A. Meju, Ian J. Ferguson, Luis Walter Daesslé, Adam Schultz, Barbara L. Sherriff, Christine Stumpp, Thomas Kretzschmar and Kay Knöller and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Geophysics.

In The Last Decade

M. A. Pérez‐Flores

42 papers receiving 521 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. A. Pérez‐Flores Mexico 13 438 252 73 61 58 44 535
A. Steuer Germany 12 334 0.8× 268 1.1× 62 0.8× 62 1.0× 46 0.8× 27 430
Shalivahan Srivastava India 13 528 1.2× 391 1.6× 38 0.5× 83 1.4× 84 1.4× 27 654
Alexandros Stampolidis Greece 13 351 0.8× 156 0.6× 29 0.4× 32 0.5× 94 1.6× 44 482
Richard Krahenbuhl United States 15 511 1.2× 270 1.1× 96 1.3× 131 2.1× 35 0.6× 54 676
Hesham El‐Kaliouby Egypt 12 296 0.7× 243 1.0× 43 0.6× 44 0.7× 33 0.6× 31 380
M. Israil India 15 572 1.3× 405 1.6× 177 2.4× 18 0.3× 38 0.7× 42 804
A. Manglik India 18 419 1.0× 120 0.5× 224 3.1× 22 0.4× 33 0.6× 73 707
Çağlayan Balkaya Türkiye 20 777 1.8× 547 2.2× 60 0.8× 172 2.8× 154 2.7× 43 909
Jorge A. Arzate Mexico 14 438 1.0× 84 0.3× 41 0.6× 11 0.2× 58 1.0× 29 575
Joan Campanyà Ireland 16 415 0.9× 123 0.5× 51 0.7× 25 0.4× 30 0.5× 32 540

Countries citing papers authored by M. A. Pérez‐Flores

Since Specialization
Citations

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

Fields of papers citing papers by M. A. Pérez‐Flores

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. A. Pérez‐Flores. 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 M. A. Pérez‐Flores. The network helps show where M. A. Pérez‐Flores may publish in the future.

Co-authorship network of co-authors of M. A. Pérez‐Flores

This figure shows the co-authorship network connecting the top 25 collaborators of M. A. Pérez‐Flores. A scholar is included among the top collaborators of M. A. Pérez‐Flores 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 M. A. Pérez‐Flores. M. A. Pérez‐Flores 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.
Liotta, Domenico, Luigi Piccardi, Andrea Brogi, et al.. (2024). Gravimetric and morpho-structural analyses in the superhot geothermal system Los Humeros: an example from central Mexico. Geothermal Energy. 12(1). 4 indexed citations
2.
Pérez‐Flores, M. A., et al.. (2023). Density and magnetization models for the Acoculco geothermal field by joint 3D inversion. Geothermics. 117. 102869–102869. 1 indexed citations
3.
González‐Fernández, Antonio, et al.. (2023). Fluid-rock mineral equilibrium and new improved Na/K geothermometers: The case of the Cerro Prieto geothermal field (CP-I), Mexico. Geothermics. 115. 102822–102822. 1 indexed citations
4.
Pérez‐Flores, M. A., et al.. (2021). Joint inversion of gravity and magnetic data using correspondence maps with application to geothermal fields. Geophysical Journal International. 228(3). 1621–1636. 9 indexed citations
5.
Pérez‐Flores, M. A., et al.. (2021). Contribution of ERT on the Study of Ag-Pb-Zn, Fluorite, and Barite Deposits in Northeast Mexico. Minerals. 11(3). 249–249. 6 indexed citations
6.
Pérez‐Flores, M. A., et al.. (2019). Three-dimensional inverse modeling of EM-LIN data for the exploration of coastal sinkholes in Quintana Roo, Mexico. Natural hazards and earth system sciences. 19(8). 1779–1787. 3 indexed citations
7.
Pérez‐Flores, M. A., et al.. (2018). 3D Inverse modeling of EM-LIN data to investigate coastal sinkholes in Quintana Roo Mexico. Biogeosciences (European Geosciences Union). 1 indexed citations
8.
Pérez‐Flores, M. A., et al.. (2014). Structural deformation in central Cuba and implications for the petroleum system: new insights from 3D inversion of gravity data. SHILAP Revista de lepidopterología. 1 indexed citations
9.
Pérez‐Flores, M. A., et al.. (2014). ELECTROMAGNETIC METHODS APPLICATION FOR CHARACTERIZING A SITE CONTAMINATED BY LEACHATES. Revista Internacional de Contaminación Ambiental. 30(3). 317–329. 5 indexed citations
10.
Pérez‐Flores, M. A. & Adam Schultz. (2014). Application of 2-D inversion with genetic algorithms to magnetotelluric data from geothermal areas. Earth Planets and Space. 54(5). 607–616. 11 indexed citations
11.
Pérez‐Flores, M. A., et al.. (2012). Imaging of 3D electromagnetic data at low-induction numbers. Geophysics. 77(4). WB47–WB57. 21 indexed citations
12.
Pérez‐Flores, M. A., et al.. (2007). Geometry of ophiolites in eastern Cuba from 3D inversion of aeromagnetic data, constrained by surface geology. Geophysics. 72(3). B81–B91. 6 indexed citations
13.
Pérez‐Flores, M. A. & Enrique Gómez‐Treviño. (2005). Tridimensional Inversion of DC Resistivity Data. 3 indexed citations
14.
Pérez‐Flores, M. A., et al.. (2005). Computational study of seismic waves in homogeneous dynamic‐porosity media with thermal and fluid relaxation: Gauging Biot theory. Journal of Geophysical Research Atmospheres. 110(B7). 9 indexed citations
15.
Gallardo, Luis A., Max A. Meju, & M. A. Pérez‐Flores. (2005). A quadratic programming approach for joint image reconstruction: mathematical and geophysical examples. Inverse Problems. 21(2). 435–452. 25 indexed citations
16.
Gallardo, Luis A., M. A. Pérez‐Flores, & Enrique Gómez‐Treviño. (2003). A versatile algorithm for joint 3D inversion of gravity and magnetic data. Geophysics. 68(3). 949–959. 112 indexed citations
17.
Gómez‐Treviño, Enrique, et al.. (2002). Forward modelling of direct current and low-frequency electromagnetic fields using integral equations. Geophysical Journal International. 137(2). 336–352. 26 indexed citations
18.
Pérez‐Flores, M. A., et al.. (2001). Imaging low-frequency and dc electromagnetic fields using a simple linear approximation. Geophysics. 66(4). 1067–1081. 53 indexed citations
19.
Gómez‐Treviño, Enrique, et al.. (2001). Electrical structure of the Baja California lithosphere beneath Vizcaíno region. AGUFM. 2001. 1 indexed citations
20.
Pérez‐Flores, M. A., et al.. (1993). A Simple Method of Magnetotelluric Inversion in Two Dimensions. 3 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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