S. Valero

118 total papers · 2.5k total citations
71 papers, 1.8k citations indexed

About

S. Valero is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, S. Valero has authored 71 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Electrical and Electronic Engineering, 12 papers in Computer Networks and Communications and 12 papers in Artificial Intelligence. Recurrent topics in S. Valero's work include Energy Load and Power Forecasting (26 papers), Smart Grid Energy Management (11 papers) and Advanced Wireless Communication Techniques (11 papers). S. Valero is often cited by papers focused on Energy Load and Power Forecasting (26 papers), Smart Grid Energy Management (11 papers) and Advanced Wireless Communication Techniques (11 papers). S. Valero collaborates with scholars based in Spain, United States and Italy. S. Valero's co-authors include Antonia M. Tulino, Antonio Gabaldón, C. Senabre, F.J.G. Franco, H. Vincent Poor, Carlos Álvarez-Bel, Mario Ortíz, Siu‐Wai Ho, Juan Aparicio and Antonio Guillamón and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Information Theory and IEEE Transactions on Power Systems.

In The Last Decade

S. Valero

65 papers receiving 1.7k citations

Hit Papers

Random Matrix Theory and ... 2004 2026 2011 2018 2004 200 400 600

Author Peers

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

Author Last Decade Papers Cites
S. Valero 1.2k 577 248 155 153 71 1.8k
Maurizio A. Spirito 848 0.7× 1.1k 2.0× 286 1.2× 79 0.5× 413 2.7× 73 1.7k
Jens Vygen 933 0.8× 652 1.1× 284 1.1× 102 0.7× 76 0.5× 73 2.2k
Yacine Chakhchoukh 688 0.6× 340 0.6× 283 1.1× 628 4.1× 216 1.4× 52 1.3k
D. K. Lobiyal 998 0.8× 1.3k 2.3× 300 1.2× 62 0.4× 57 0.4× 154 1.9k
Zhiyuan Xu 541 0.4× 807 1.4× 523 2.1× 202 1.3× 62 0.4× 49 2.1k
Seung-Jun Kim 1.2k 1.0× 848 1.5× 129 0.5× 136 0.9× 212 1.4× 88 1.7k
Glen Takahara 809 0.7× 948 1.6× 221 0.9× 67 0.4× 41 0.3× 78 1.4k
Kishan G. Mehrotra 300 0.2× 230 0.4× 732 3.0× 163 1.1× 151 1.0× 83 1.9k
Chao Chen 504 0.4× 990 1.7× 338 1.4× 200 1.3× 167 1.1× 106 1.5k
Jun Liang 439 0.4× 249 0.4× 413 1.7× 270 1.7× 95 0.6× 84 1.4k

Countries citing papers authored by S. Valero

Since Specialization
Citations

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

Fields of papers citing papers by S. Valero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Valero

This figure shows the co-authorship network connecting the top 25 collaborators of S. Valero. A scholar is included among the top collaborators of S. Valero 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 S. Valero. S. Valero 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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