Fernando Sánchez-Figueroa

1.2k total citations
58 papers, 604 citations indexed

About

Fernando Sánchez-Figueroa is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Fernando Sánchez-Figueroa has authored 58 papers receiving a total of 604 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Information Systems, 22 papers in Artificial Intelligence and 10 papers in Computer Networks and Communications. Recurrent topics in Fernando Sánchez-Figueroa's work include Service-Oriented Architecture and Web Services (30 papers), Web Applications and Data Management (20 papers) and Advanced Software Engineering Methodologies (17 papers). Fernando Sánchez-Figueroa is often cited by papers focused on Service-Oriented Architecture and Web Services (30 papers), Web Applications and Data Management (20 papers) and Advanced Software Engineering Methodologies (17 papers). Fernando Sánchez-Figueroa collaborates with scholars based in Spain, Italy and United States. Fernando Sánchez-Figueroa's co-authors include Juan Carlos Preciado, Marino Linaje, José M. Conejero, Sara Comai, Roberto Rodríguez-Echeverría, Gustavo Rossi, Piero Fraternali, Juan Hernández, Enrique Moguel and Juan Boubeta‐Puig and has published in prestigious journals such as IEEE Access, Sensors and Journal of the Association for Information Systems.

In The Last Decade

Fernando Sánchez-Figueroa

56 papers receiving 537 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fernando Sánchez-Figueroa Spain 12 377 132 89 79 73 58 604
Juan Carlos Preciado Spain 11 258 0.7× 72 0.5× 50 0.6× 46 0.6× 62 0.8× 38 468
Huan Huo Australia 15 220 0.6× 265 2.0× 84 0.9× 32 0.4× 31 0.4× 49 563
Muzammil Khan Pakistan 12 134 0.4× 160 1.2× 68 0.8× 21 0.3× 38 0.5× 51 430
Francisco Ortín Spain 14 337 0.9× 381 2.9× 146 1.6× 122 1.5× 16 0.2× 89 778
Chhabi Rani Panigrahi India 15 205 0.5× 113 0.9× 311 3.5× 56 0.7× 47 0.6× 72 612
Muhammad Abbas Pakistan 13 118 0.3× 95 0.7× 61 0.7× 43 0.5× 12 0.2× 52 451
Zhiling Luo China 14 155 0.4× 112 0.8× 160 1.8× 11 0.1× 39 0.5× 44 465
Yazan A. Alsariera Saudi Arabia 11 179 0.5× 170 1.3× 127 1.4× 72 0.9× 20 0.3× 31 449
Sidi Mohamed Benslimane Algeria 10 172 0.5× 149 1.1× 108 1.2× 9 0.1× 28 0.4× 83 365
Yahya Tashtoush Jordan 11 109 0.3× 166 1.3× 113 1.3× 34 0.4× 37 0.5× 43 398

Countries citing papers authored by Fernando Sánchez-Figueroa

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Sánchez-Figueroa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Sánchez-Figueroa. 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 Fernando Sánchez-Figueroa. The network helps show where Fernando Sánchez-Figueroa may publish in the future.

Co-authorship network of co-authors of Fernando Sánchez-Figueroa

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Sánchez-Figueroa. A scholar is included among the top collaborators of Fernando Sánchez-Figueroa 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 Fernando Sánchez-Figueroa. Fernando Sánchez-Figueroa 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.
Bas, María, et al.. (2024). A multi-criteria decision support system to evaluate the effectiveness of training courses on citizens’ employability. Applied Intelligence. 55(1). 1 indexed citations
2.
Sánchez-Figueroa, Fernando, et al.. (2022). The Use of Salvage Procedures for Wound Complications in Neuromodulation. World Neurosurgery. 171. e596–e604. 1 indexed citations
3.
Preciado, Juan Carlos, et al.. (2021). A Real-Life Machine Learning Experience for Predicting University Dropout at Different Stages Using Academic Data. IEEE Access. 9. 133076–133090. 33 indexed citations
4.
Rodríguez-Echeverría, Roberto, et al.. (2020). Creating a Recommender System to Support Higher Education Students in the Subject Enrollment Decision. IEEE Access. 8. 189069–189088. 31 indexed citations
5.
Benı́tez, Rafael, et al.. (2019). A Short-Term Data Based Water Consumption Prediction Approach. Energies. 12(12). 2359–2359. 20 indexed citations
6.
Conejero, José M., et al.. (2018). Early evaluation of technical debt impact on maintainability. Journal of Systems and Software. 142. 92–114. 11 indexed citations
7.
Preciado, Juan Carlos, et al.. (2018). An Approach for Guesstimating the Deployment Cost in Cloud Infrastructures at Design Phase in Web Engineering.. Journal of Web Engineering. 17. 224–240. 1 indexed citations
8.
Rodríguez-Echeverría, Roberto, et al.. (2018). AutoCRUD: Automatic generation of CRUD specifications in interaction flow modelling language. Science of Computer Programming. 168. 165–168. 8 indexed citations
9.
Linaje, Marino, et al.. (2015). A semantic approach for designing Assistive Software Recommender systems. Journal of Systems and Software. 104. 166–178. 6 indexed citations
10.
Moguel, Enrique, Juan Carlos Preciado, Fernando Sánchez-Figueroa, Miguel A. Preciado, & Juan Hernández. (2015). Multilayer Big Data Architecture for Remote Sensing in Eolic Parks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 8(10). 4714–4719. 7 indexed citations
11.
Rodríguez-Echeverría, Roberto, et al.. (2014). IFML-based Model-Driven Front-End Modernization. Journal of the Association for Information Systems. 5 indexed citations
12.
Rodríguez-Echeverría, Roberto, et al.. (2012). Generation of WebML hypertext models from legacy Web Applications. 91–95. 3 indexed citations
13.
Linaje, Marino, Juan Carlos Preciado, & Fernando Sánchez-Figueroa. (2010). Multi-Device Context-Aware RIAs Using a Model-Driven Approach. JUCS - Journal of Universal Computer Science. 16. 2038–2059. 3 indexed citations
14.
Preciado, Juan Carlos, Marino Linaje, & Fernando Sánchez-Figueroa. (2008). Adapting Web 1.0 User Interfaces to Web 2.0 Multidevice User Interfaces using RUX-Method. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
15.
Preciado, Juan Carlos, Marino Linaje, & Fernando Sánchez-Figueroa. (2008). Enriching model-based web applications presentation. Journal of Web Engineering. 7(3). 239–256. 4 indexed citations
16.
Preciado, Juan Carlos, Marino Linaje, & Fernando Sánchez-Figueroa. (2007). An Approach to Support the Web User Interfaces Evolution.. 6 indexed citations
17.
Kozlenkov, Alexander, et al.. (2006). A framework for architecture-driven service discovery. 67–73. 6 indexed citations
18.
Lozano-Tello, Adolfo, et al.. (2003). Uso de ontologías en páginas web para mejorar su accesibilidad a invidentes.. 625–634. 1 indexed citations
19.
Papathomas, Michael, Juan Hernández, Juan M. Murillo, & Fernando Sánchez-Figueroa. (1997). Inheritance and Expressive power in Concurrent Object-Oriented Programming.. 14. 45–60. 3 indexed citations
20.
Sánchez-Figueroa, Fernando. (1993). Loading, electromyograph, and motion during exercise. NASA Technical Reports Server (NASA). 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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