Fernando Rubio

1.4k citations
80 papers · 592 · h-index 14

Impact in

Papers in

    • Metaheuristic Optimization Algorithms Research 13
    • Evolutionary Algorithms and Applications 9
    • Logic, programming, and type systems 6
    • Machine Learning and Algorithms 6
    • Multi-Agent Systems and Negotiation 5
    • Computability, Logic, AI Algorithms 6

Fernando Rubio

69 papers receiving 545 citations

Peers

Fernando Rubio
Comparison fields: 5 of 103
  • Hardware and Architecture 62
  • Software 28
  • Artificial Intelligence 216
  • Computational Theory and Mathematics 81
  • Life-span and Life-course Studies 4
Replace Daniel W. Lewis with:
Daniel W. Lewis United States
Thomas Ottmann Germany
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Citations per field
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Citations per year

Countries citing papers authored by Fernando Rubio

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Rubio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Fernando Rubio, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fernando Rubio Line = papers co-authored together Fernando Rubio links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200777
2 200342
3 202136
4 198632
5 201223
6 201520
7 200819
8 201417
9 200517
10 200817
11 201716
12 201315
13 201214
14 202113
15 201712
16 200411
17 201910
18 200310
19 200310
20 20169

About Fernando Rubio

Fernando Rubio is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Hardware and Architecture and Management Science and Operations Research, having authored 80 papers that have together received 592 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (13 papers), Evolutionary Algorithms and Applications (9 papers), Auction Theory and Applications (8 papers), Parallel Computing and Optimization Techniques (8 papers), Logic, programming, and type systems (6 papers), Computability, Logic, AI Algorithms (6 papers), Machine Learning and Algorithms (6 papers) and Multi-Agent Systems and Negotiation (5 papers). The work is most often cited by research in Hardware and Architecture (62 citations), Software (28 citations), Artificial Intelligence (216 citations), Computational Theory and Mathematics (81 citations) and Life-span and Life-course Studies (4 citations). Fernando Rubio has collaborated with scholars based in Spain, Germany and Canada. Frequent co-authors include Ismael Rodrı́guez, Pablo Rabanal, Manuel Núñez, Ricardo Peña, César Nombela, Rafael Rotger, Phil Trinder, Jorge Enrique Correa‐Bautista, Greg Michaelson and Stefan Priebe. Their work appears in journals such as Journal of Computational Science, Software Testing Verification and Reliability, Formal Aspects of Computing, Frontiers of Computer Science and Applied Soft Computing.

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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