Salvador Pintos

1.5k total citations
25 papers, 1.2k citations indexed

About

Salvador Pintos is a scholar working on Computational Theory and Mathematics, Ocean Engineering and Statistics, Probability and Uncertainty. According to data from OpenAlex, Salvador Pintos has authored 25 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computational Theory and Mathematics, 12 papers in Ocean Engineering and 7 papers in Statistics, Probability and Uncertainty. Recurrent topics in Salvador Pintos's work include Advanced Multi-Objective Optimization Algorithms (15 papers), Reservoir Engineering and Simulation Methods (12 papers) and Probabilistic and Robust Engineering Design (7 papers). Salvador Pintos is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (15 papers), Reservoir Engineering and Simulation Methods (12 papers) and Probabilistic and Robust Engineering Design (7 papers). Salvador Pintos collaborates with scholars based in Venezuela, United States and Spain. Salvador Pintos's co-authors include Néstor V. Queipo, Luis E. Zerpa, Luis J. Mena, Gladys E. Maestre, Tulio Sulbarán, Jean‐Louis Salager, Javier V. Goicochea, Enrique Carrero, M. Morcillo and Oladis Troconis de Rincón and has published in prestigious journals such as Corrosion Science, Journal of Hypertension and Journal of Petroleum Science and Engineering.

In The Last Decade

Salvador Pintos

25 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Salvador Pintos Venezuela 13 353 320 290 264 192 25 1.2k
Warren Smith Australia 16 38 0.1× 113 0.4× 58 0.2× 243 0.9× 45 0.2× 63 896
Sei-ichiro SAKATA Japan 23 16 0.0× 370 1.2× 254 0.9× 441 1.7× 375 2.0× 124 1.8k
Josep Vehı́ Spain 29 33 0.1× 219 0.7× 151 0.5× 122 0.5× 71 0.4× 159 2.8k
Qibin Wang China 28 111 0.3× 25 0.1× 1.5k 5.1× 57 0.2× 109 0.6× 87 2.7k
Xianghong Ma United Kingdom 21 22 0.1× 85 0.3× 83 0.3× 29 0.1× 63 0.3× 70 1.1k
Klaas Visser Netherlands 24 234 0.7× 206 0.6× 156 0.5× 10 0.0× 46 0.2× 72 2.4k
Samuel H. Brooks United States 17 19 0.1× 216 0.7× 34 0.1× 93 0.4× 50 0.3× 29 811
Duck‐Joo Lee South Korea 18 104 0.3× 20 0.1× 69 0.2× 40 0.2× 37 0.2× 103 1.1k
Marco Cavazzuti Italy 13 24 0.1× 13 0.0× 310 1.1× 96 0.4× 32 0.2× 42 982

Countries citing papers authored by Salvador Pintos

Since Specialization
Citations

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

Fields of papers citing papers by Salvador Pintos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Salvador Pintos

This figure shows the co-authorship network connecting the top 25 collaborators of Salvador Pintos. A scholar is included among the top collaborators of Salvador Pintos 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 Salvador Pintos. Salvador Pintos 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.
Queipo, Néstor V., et al.. (2012). Setting targets for surrogate-based optimization. Journal of Global Optimization. 55(4). 857–875. 7 indexed citations
2.
Queipo, Néstor V., et al.. (2010). Setting Targets for Surrogate-Based Optimization. 2 indexed citations
3.
Queipo, Néstor V., et al.. (2009). Assessing the value of another cycle in Gaussian process surrogate-based optimization. Structural and Multidisciplinary Optimization. 39(5). 459–475. 15 indexed citations
4.
Zerpa, Luis E., et al.. (2008). An efficient response surface approach for the optimization of ASP flooding processes. Revista Tecnica De La Facultad De Ingenieria Universidad Del Zulia. 31. 50–60. 4 indexed citations
5.
Pintos, Salvador, et al.. (2007). Toward an optimal ensemble of kernel-based approximations with engineering applications. Structural and Multidisciplinary Optimization. 36(3). 247–261. 83 indexed citations
6.
Carrero, Enrique, Néstor V. Queipo, Salvador Pintos, & Luis E. Zerpa. (2007). Global sensitivity analysis of Alkali–Surfactant–Polymer enhanced oil recovery processes. Journal of Petroleum Science and Engineering. 58(1-2). 30–42. 90 indexed citations
7.
8.
Queipo, Néstor V., et al.. (2006). Assessing the Value of Another Cycle in Surrogate-based Optimization. 1 indexed citations
9.
Zerpa, Luis E., Néstor V. Queipo, Salvador Pintos, & Jean‐Louis Salager. (2005). An optimization methodology of alkaline–surfactant–polymer flooding processes using field scale numerical simulation and multiple surrogates. Journal of Petroleum Science and Engineering. 47(3-4). 197–208. 262 indexed citations
10.
Mena, Luis J., et al.. (2005). A reliable index for the prognostic significance of blood pressure variability. Journal of Hypertension. 23(3). 505–511. 395 indexed citations
11.
Queipo, Néstor V., et al.. (2004). The integration of design of experiments, surrogate modeling and optimization for thermoscience research. Engineering With Computers. 20(4). 309–315. 9 indexed citations
12.
Queipo, Néstor V., et al.. (2003). A model for the integrated optimization of oil production systems. Engineering With Computers. 19(2-3). 130–141. 4 indexed citations
13.
Queipo, Néstor V., et al.. (2002). Surrogate modeling-based optimization for the integration of static and dynamic data into a reservoir description. Journal of Petroleum Science and Engineering. 35(3-4). 167–181. 34 indexed citations
14.
Queipo, Néstor V., Javier V. Goicochea, & Salvador Pintos. (2002). Surrogate modeling-based optimization of SAGD processes. Journal of Petroleum Science and Engineering. 35(1-2). 83–93. 73 indexed citations
15.
Queipo, Néstor V., et al.. (2002). Efficient Global Optimization for Hydraulic Fracturing Treatment Design. 4 indexed citations
16.
Queipo, Néstor V., et al.. (2001). Surrogate Modeling-Based Optimization of SAGD Processes. 15 indexed citations
17.
Pintos, Salvador, et al.. (2000). Artificial neural network modeling of atmospheric corrosion in the MICAT project. Corrosion Science. 42(1). 35–52. 74 indexed citations
18.
Queipo, Néstor V., et al.. (2000). Surrogate Modeling-Based Optimization for the Integration of Static and Dynamic Data Into a Reservoir Description. SPE Annual Technical Conference and Exhibition. 22 indexed citations
19.
20.
Pintos, Salvador, et al.. (1986). On differentiable exact penalty functions. Journal of Optimization Theory and Applications. 50(3). 479–493. 2 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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