Ernesto Costa

2.8k total citations · 1 hit paper
102 papers, 1.2k citations indexed

About

Ernesto Costa is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Ernesto Costa has authored 102 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Artificial Intelligence, 15 papers in Computational Theory and Mathematics and 11 papers in Molecular Biology. Recurrent topics in Ernesto Costa's work include Evolutionary Algorithms and Applications (44 papers), Metaheuristic Optimization Algorithms Research (35 papers) and Advanced Multi-Objective Optimization Algorithms (11 papers). Ernesto Costa is often cited by papers focused on Evolutionary Algorithms and Applications (44 papers), Metaheuristic Optimization Algorithms Research (35 papers) and Advanced Multi-Objective Optimization Algorithms (11 papers). Ernesto Costa collaborates with scholars based in Portugal, United Kingdom and Ireland. Ernesto Costa's co-authors include Anabela Simões, Francisco B. Pereira, Sara Silva, Jorge Tavares, Penousal Machado, Nuno Lourenço, Marco Vieira, Lino Marques, Eugénia Cunha and David Navega and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Ernesto Costa

94 papers receiving 1.1k citations

Hit Papers

Progress in Brain Research, vol 16. 1966 2026 1986 2006 1966 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ernesto Costa Portugal 17 496 208 185 162 130 102 1.2k
Taewan Kim South Korea 21 212 0.4× 163 0.8× 188 1.0× 51 0.3× 34 0.3× 113 1.1k
Chen Dong China 22 397 0.8× 106 0.5× 480 2.6× 122 0.8× 29 0.2× 138 2.5k
Changle Zhou China 24 441 0.9× 63 0.3× 109 0.6× 84 0.5× 72 0.6× 196 2.1k
Hui Lu China 19 332 0.7× 61 0.3× 365 2.0× 150 0.9× 85 0.7× 89 1.3k
Yuting Liu China 19 334 0.7× 118 0.6× 153 0.8× 55 0.3× 19 0.1× 74 1.4k
Michael A. Lones United Kingdom 17 353 0.7× 207 1.0× 29 0.2× 76 0.5× 29 0.2× 63 893
Xiaoxian He China 9 213 0.4× 263 1.3× 655 3.5× 106 0.7× 27 0.2× 17 1.2k
James P. Rice United States 22 1.3k 2.6× 342 1.6× 104 0.6× 90 0.6× 48 0.4× 37 2.2k
Ali A. Minai United States 25 547 1.1× 199 1.0× 180 1.0× 111 0.7× 39 0.3× 124 2.1k

Countries citing papers authored by Ernesto Costa

Since Specialization
Citations

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

Fields of papers citing papers by Ernesto Costa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ernesto Costa

This figure shows the co-authorship network connecting the top 25 collaborators of Ernesto Costa. A scholar is included among the top collaborators of Ernesto Costa 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 Ernesto Costa. Ernesto Costa 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.
Costa, Ernesto, et al.. (2022). Online Failure Prediction for Complex Systems: Methodology and Case Studies. IEEE Transactions on Dependable and Secure Computing. 20(4). 3520–3534. 2 indexed citations
2.
Navega, David, Ernesto Costa, & Eugénia Cunha. (2022). Adult Skeletal Age-at-Death Estimation through Deep Random Neural Networks: A New Method and Its Computational Analysis. Biology. 11(4). 532–532. 21 indexed citations
3.
Martins, Tiago, João Correia, Ernesto Costa, & Penousal Machado. (2019). Evolving Stencils for Typefaces: Combining Machine Learning, User’s Preferences and Novelty. Complexity. 2019(1). 1 indexed citations
4.
Costa, Ernesto, et al.. (2019). Improving Failure Prediction by Ensembling the Decisions of Machine Learning Models: A Case Study. IEEE Access. 7. 177661–177674. 11 indexed citations
5.
Marques, Lino, et al.. (2019). A Comparative Study of Bio-Inspired Odour Source Localisation Strategies from the State-Action Perspective. Sensors. 19(10). 2231–2231. 19 indexed citations
6.
Machado, Penousal, et al.. (2015). Progress in Artificial Intelligence: 17th Portuguese Conference on Artificial Intelligence, EPIA 2015, Coimbra, Portugal, September 8-11, 2015. Springer eBooks. 1 indexed citations
7.
Costa, Ernesto, et al.. (2010). EPIAL - An Epigenetic Approach for an Artificial Life Model. 90–97. 1 indexed citations
8.
Gonçalves, Ângela & Ernesto Costa. (2008). A Computational Model of Gene Regulatory Networks and its Topological Properties.. Artificial Life. 204–211. 3 indexed citations
9.
Silva, Sara & Ernesto Costa. (2004). Dynamic Limits for Bloat Control: Variations on Size and Depth.. Genetic and Evolutionary Computation Conference. 666–677. 22 indexed citations
10.
Keijzer, Maarten, Una-May O’Reilly, Simon M. Lucas, Ernesto Costa, & Terence Soule. (2004). Genetic Programming: 7th European Conference, Eurogp2004, Coimbra, Portugal, April 5-7, 2004, Proceedings (LECTURE NOTES IN COMPUTER SCIENCE). Springer eBooks. 2 indexed citations
11.
Simões, Anabela & Ernesto Costa. (2002). Using GAs To Deal With Dynamic Environments: A Comparative Study Of Several Approaches Based On Promoting Diversity. Genetic and Evolutionary Computation Conference. 698–698. 6 indexed citations
12.
Machado, Penousal, Jorge Tavares, Francisco B. Pereira, & Ernesto Costa. (2002). Vehicle Routing Problem: doing it the evolutionary way. Genetic and Evolutionary Computation Conference. 690–690. 29 indexed citations
13.
Simões, Anabela & Ernesto Costa. (2002). Parametric Study To Enhance The Genetic Algorithm's Performance When Using Transformation. Genetic and Evolutionary Computation Conference. 697–697. 7 indexed citations
14.
Pereira, Francisco B. & Ernesto Costa. (2001). Understanding the role of learning in the evolution of busy beavers: a comparison between the baldwin effect and a Lamarckian strategy. Genetic and Evolutionary Computation Conference. 884–891. 1 indexed citations
15.
Santana, Roberto, et al.. (2000). Probabilistic evolution and the Busy Beaver problem. Genetic and Evolutionary Computation Conference. 380–380. 3 indexed citations
16.
Simões, Anabela & Ernesto Costa. (2000). Using genetic algorithms with asexual transposition. Genetic and Evolutionary Computation Conference. 323–330. 9 indexed citations
17.
Simões, Anabela & Ernesto Costa. (1999). Transposition versus crossover: an empirical study. Genetic and Evolutionary Computation Conference. 612–619. 25 indexed citations
18.
Pereira, Francisco B., Penousal Machado, & Ernesto Costa. (1999). Graph Based Crossover - A Case Study with the Busy Beaver Problem. 20 indexed citations
19.
Costa, Ernesto, et al.. (1996). Nueva formula matemática para el calculo de la proteinuria de 24 horas en niños. SHILAP Revista de lepidopterología. 1 indexed citations
20.
Kodratoff, Yves, et al.. (1986). Méthode de transformation de programmes de Burstall-Darlington appliquée à la programmation logique.. 327–344. 1 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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