Carlos Ansótegui

2.0k total citations
51 papers, 525 citations indexed

About

Carlos Ansótegui is a scholar working on Computer Networks and Communications, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Carlos Ansótegui has authored 51 papers receiving a total of 525 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Networks and Communications, 25 papers in Artificial Intelligence and 24 papers in Computational Theory and Mathematics. Recurrent topics in Carlos Ansótegui's work include Constraint Satisfaction and Optimization (25 papers), Formal Methods in Verification (19 papers) and Logic, Reasoning, and Knowledge (13 papers). Carlos Ansótegui is often cited by papers focused on Constraint Satisfaction and Optimization (25 papers), Formal Methods in Verification (19 papers) and Logic, Reasoning, and Knowledge (13 papers). Carlos Ansótegui collaborates with scholars based in Spain, United States and United Kingdom. Carlos Ansótegui's co-authors include Jordi Levy, Marı́a Luisa Bonet, Felip Manyà, Meinolf Sellmann, Yuri Malitsky, Cèsar Fernández, Kevin Tierney, Carla P. Gomes, Mateu Villaret and Miquel Bofill and has published in prestigious journals such as Information Sciences, Artificial Intelligence and Fuzzy Sets and Systems.

In The Last Decade

Carlos Ansótegui

46 papers receiving 499 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Carlos Ansótegui Spain 14 316 252 212 85 71 51 525
Kimbal George Marriott Australia 3 183 0.6× 101 0.4× 202 1.0× 72 0.8× 66 0.9× 7 433
Hans Kleine Büning Germany 12 363 1.1× 384 1.5× 147 0.7× 45 0.5× 89 1.3× 59 612
Robert Nieuwenhuis Spain 12 508 1.6× 447 1.8× 158 0.7× 35 0.4× 130 1.8× 45 700
Lakhdar Saïs France 13 347 1.1× 250 1.0× 392 1.8× 61 0.7× 64 0.9× 58 647
Gianfranco Lamperti Italy 11 181 0.6× 368 1.5× 97 0.5× 112 1.3× 53 0.7× 50 553
Spiro Michaylov United States 10 382 1.2× 173 0.7× 328 1.5× 32 0.4× 99 1.4× 21 595
Albert Oliveras Spain 9 399 1.3× 387 1.5× 173 0.8× 23 0.3× 158 2.2× 17 606
Laure Petrucci France 7 179 0.6× 364 1.4× 130 0.6× 50 0.6× 191 2.7× 38 569
Pierre Flener Sweden 11 159 0.5× 94 0.4× 143 0.7× 31 0.4× 58 0.8× 74 360
Thom Frühwirth Germany 14 586 1.9× 177 0.7× 379 1.8× 29 0.3× 161 2.3× 69 781

Countries citing papers authored by Carlos Ansótegui

Since Specialization
Citations

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

Fields of papers citing papers by Carlos Ansótegui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carlos Ansótegui

This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Ansótegui. A scholar is included among the top collaborators of Carlos Ansótegui 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 Carlos Ansótegui. Carlos Ansótegui 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.
Ansótegui, Carlos, et al.. (2023). Effectively computing high strength mixed covering arrays with constraints. Journal of Parallel and Distributed Computing. 185. 104791–104791.
2.
López-Sánchez, Maite, Juan A. Rodríguez-Aguilar, Filippo Bistaffa, et al.. (2023). Encoding Ethics to Compute Value-Aligned Norms. Minds and Machines. 33(4). 761–790. 2 indexed citations
3.
Ansótegui, Carlos, et al.. (2022). Incomplete MaxSAT approaches for combinatorial testing. Journal of Heuristics. 28(4). 377–431. 14 indexed citations
4.
Ansótegui, Carlos, et al.. (2022). Interpretable decision trees through MaxSAT. Artificial Intelligence Review. 56(8). 8303–8323. 7 indexed citations
5.
López-Sánchez, Maite, et al.. (2018). Moral Values in Norm Decision Making. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 1294–1302. 10 indexed citations
6.
Ansótegui, Carlos, Yuri Malitsky, Horst Samulowitz, Meinolf Sellmann, & Kevin Tierney. (2015). Model-based genetic algorithms for algorithm configuration. International Conference on Artificial Intelligence. 733–739. 38 indexed citations
7.
Ansótegui, Carlos, et al.. (2013). Solving (Weighted) Partial MaxSAT with ILP.. 403–409. 24 indexed citations
8.
Ansótegui, Carlos, et al.. (2011). Satisfiability Modulo Theories: An Efficient Approach for the Resource-Constrained Project Scheduling Problem. 11 indexed citations
9.
Ansótegui, Carlos & Jordi Levy. (2011). On the Modularity of Industrial SAT Instances. 232. 11–20. 2 indexed citations
10.
Ansótegui, Carlos, Marı́a Luisa Bonet, & Jordi Levy. (2009). Towards industrial-like random SAT instances. International Joint Conference on Artificial Intelligence. 387–392. 20 indexed citations
11.
Ansótegui, Carlos, Marı́a Luisa Bonet, Jordi Levy, & Felip Manyà. (2008). Measuring the hardness of SAT instances. National Conference on Artificial Intelligence. 222–228. 17 indexed citations
12.
Ansótegui, Carlos, Ramón Béjar, Cèsar Fernández, & Carles Mateu. (2008). Generating hard SAT/CSP instances using expander graphs. National Conference on Artificial Intelligence. 1442–1443.
13.
Ansótegui, Carlos, Marı́a Luisa Bonet, Jordi Levy, & Felip Manyà. (2007). What Is a Real-World SAT Instance?. 19–28. 1 indexed citations
14.
Ansótegui, Carlos, Marı́a Luisa Bonet, Jordi Levy, & Felip Manyà. (2007). Inference rules for high-order consistency in weighted CSP. National Conference on Artificial Intelligence. 167–172. 3 indexed citations
15.
Ansótegui, Carlos, Ramón Béjar, Cèsar Fernández, & Carles Mateu. (2007). On balanced CSPs with high treewidth. National Conference on Artificial Intelligence. 50(3). 161–166. 2 indexed citations
16.
Ansótegui, Carlos, Ramón Béjar, Cèsar Fernández, Carla P. Gomes, & Carles Mateu. (2006). The impact of balancing on problem hardness in a highly structured domain. National Conference on Artificial Intelligence. 10–15. 6 indexed citations
17.
Sellmann, Meinolf & Carlos Ansótegui. (2006). Disco - Novo - GoGo: integrating local search and complete search with restarts. National Conference on Artificial Intelligence. 1051–1056. 8 indexed citations
18.
Ansótegui, Carlos, Álvaro del Val, Iván Dotú, Cèsar Fernández, & Felip Manyà. (2004). Modeling choices in quasigroup completion: SAT vs. CSP. National Conference on Artificial Intelligence. 137–142. 16 indexed citations
19.
Ansótegui, Carlos & Felip Manyà. (2003). Una introducción a los algoritmos de satisfactibilidad. Redalyc (Universidad Autónoma del Estado de México). 7(20). 43–56.
20.
Alsinet, Teresa, Carlos Ansótegui, Ramón Béjar, Cèsar Fernández, & Felip Manyà. (2003). Automated monitoring of medical protocols: a secure and distributed architecture. Artificial Intelligence in Medicine. 27(3). 367–392. 16 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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