Francisco Bellas

209 total papers · 1.6k total citations
86 papers, 662 citations indexed

About

Francisco Bellas is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Francisco Bellas has authored 86 papers receiving a total of 662 indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Artificial Intelligence, 15 papers in Computer Networks and Communications and 14 papers in Information Systems. Recurrent topics in Francisco Bellas's work include Reinforcement Learning in Robotics (34 papers), Evolutionary Algorithms and Applications (29 papers) and AI-based Problem Solving and Planning (15 papers). Francisco Bellas is often cited by papers focused on Reinforcement Learning in Robotics (34 papers), Evolutionary Algorithms and Applications (29 papers) and AI-based Problem Solving and Planning (15 papers). Francisco Bellas collaborates with scholars based in Spain, Costa Rica and Denmark. Francisco Bellas's co-authors include Richard J. Duro, J. A. Becerra, Abraham Prieto, Andrés Faíña, Alberto Pan, Juan Raposo, Manuel Álvarez, Fidel Cacheda, Fernando López Peña and Rodrigo Salgado and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Information Sciences.

In The Last Decade

Francisco Bellas

80 papers receiving 605 citations

Author Peers

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

Author						Papers	Cites
Francisco Bellas	326	148	102	90	84	86	662
Leon Reznik	305 0.9×	89 0.6×	174 1.7×	50 0.6×	175 2.1×	99	705
Jingchao Sun	230 0.7×	239 1.6×	219 2.1×	62 0.7×	117 1.4×	43	779
Barry Fagin	140 0.4×	126 0.9×	95 0.9×	83 0.9×	63 0.8×	63	675
Douglas Blank	216 0.7×	81 0.5×	51 0.5×	102 1.1×	138 1.6×	47	737
Jianrong Wang	223 0.7×	125 0.8×	110 1.1×	27 0.3×	125 1.5×	87	722
Kirstie L. Bellman	427 1.3×	183 1.2×	221 2.2×	63 0.7×	57 0.7×	83	729
Lisa Meeden	321 1.0×	59 0.4×	53 0.5×	152 1.7×	195 2.3×	44	754
Boško Nikolić	255 0.8×	113 0.8×	120 1.2×	19 0.2×	56 0.7×	60	703
Joaquim Filipe	181 0.6×	190 1.3×	112 1.1×	32 0.4×	51 0.6×	98	641
Yeh-Cheng Chen	229 0.7×	221 1.5×	181 1.8×	20 0.2×	44 0.5×	68	688

Countries citing papers authored by Francisco Bellas

Since Specialization

Citations

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

Fields of papers citing papers by Francisco Bellas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francisco Bellas

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