Carlos Soares

6.0k total citations · 1 hit paper
126 papers, 2.9k citations indexed

About

Carlos Soares is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Carlos Soares has authored 126 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Artificial Intelligence, 26 papers in Information Systems and 18 papers in Signal Processing. Recurrent topics in Carlos Soares's work include Machine Learning and Data Classification (40 papers), Data Mining Algorithms and Applications (19 papers) and Machine Learning and Algorithms (12 papers). Carlos Soares is often cited by papers focused on Machine Learning and Data Classification (40 papers), Data Mining Algorithms and Applications (19 papers) and Machine Learning and Algorithms (12 papers). Carlos Soares collaborates with scholars based in Portugal, Brazil and United States. Carlos Soares's co-authors include Pavel Brazdil, Alípio Jorge, João Mendes‐Moreira, Jorge Freire de Sousa, André C. P. L. F. de Carvalho, Joaquim Pinto da Costa, Christophe Giraud-Carrier, Ricardo Vilalta, François Grosjean and André Luis Debiaso Rossi and has published in prestigious journals such as The Journal of the Acoustical Society of America, Expert Systems with Applications and Neuropsychologia.

In The Last Decade

Carlos Soares

117 papers receiving 2.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Ensemble approaches for regression

2012 485 citations João Mendes‐Moreira, Carlos Soares et al. profile →

Peers

Carlos Soares

AI

IS

CVPR

MSOR

CTM

Simon Colton United Kingdom

Lakhmi C. Jain Australia

David Camacho Spain

Ian Watson United Kingdom

Ah‐Hwee Tan Singapore

Lakhmi C. Jain Australia

Giovanni Acampora Italy

Aytuğ Onan Türkiye

Mohammed Berrada Morocco

Ramón Sangüesa Spain

Simon Colton United Kingdom

Carlos Soares

1.2k ×0.8

AI

344 ×0.9

IS

356 ×1.4

CVPR

207 ×0.8

MSOR

194 ×0.8

CTM

Citations per year, relative to Carlos Soares Carlos Soares (= 1×) peers Simon Colton

Countries citing papers authored by Carlos Soares

Since Specialization

Citations

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

Fields of papers citing papers by Carlos Soares

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carlos Soares

This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Soares. A scholar is included among the top collaborators of Carlos Soares 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 Soares. Carlos Soares is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Soares, Carlos, et al.. (2025). Shapley value-based data valuation for machine learning data markets. Discover Applied Sciences. 7(12).

2.

Ribeiro, Joël, Tânia Fontes, Carlos Soares, & José Borges. (2024). Multidimensional subgroup discovery on event logs. Expert Systems with Applications. 246. 123205–123205.

3.

Soares, Carlos, et al.. (2024). 5PSQ-120 Pembrolizumab immune-mediated toxicity. A219.2–A220.

4.

Duarte, Bárbara, Paulo César Paiva, Carlos Soares, et al.. (2024). Current distribution of the African citrus psyllid Trioza erytreae in Portugal: relation to climatic conditions. Acta Horticulturae. 423–428. 2 indexed citations

5.

Soares, Carlos, et al.. (2023). Federated Learning for Computer-Aided Diagnosis of Glaucoma Using Retinal Fundus Images. Applied Sciences. 13(21). 11620–11620. 6 indexed citations

6.

Cerqueira, Vítor, Luı́s Torgo, & Carlos Soares. (2023). Early anomaly detection in time series: a hierarchical approach for predicting critical health episodes. Machine Learning. 112(11). 4409–4430. 3 indexed citations

7.

Santos, Miriam Seoane, Pedro Henriques Abreu, Nathalie Japkowicz, et al.. (2022). On the joint-effect of class imbalance and overlap: a critical review. Artificial Intelligence Review. 55(8). 6207–6275. 70 indexed citations

8.

Soares, Carlos, et al.. (2022). Machine Learning Data Markets: Trading Data using a Multi-Agent System. 2014. 450–457. 2 indexed citations

9.

Ribeiro, Joël, Tânia Fontes, Carlos Soares, & José Borges. (2021). Accessibility as an indicator to estimate social exclusion in public transport. Transportation research procedia. 52. 740–747. 16 indexed citations

10.

Carreiro, André V., et al.. (2020). Fraunhofer AICOS at CLEF eHealth 2020 Task 1: Clinical Code Extraction From Textual Data Using Fine-Tuned BERT Models.. CLEF (Working Notes). 4 indexed citations

11.

Garcia, Luís P. F., et al.. (2018). Towards Reproducible Empirical Research in Meta-Learning.. arXiv (Cornell University). 7 indexed citations

12.

Sá, Cláudio Rebelo de, Paulo J. Azevedo, Carlos Soares, Alípio Jorge, & Arno Knobbe. (2017). Preference Rules for Label Ranking: Mining Patterns in Multi-Target Relations. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 3 indexed citations

13.

Cruz, Luís, et al.. (2015). A Comparative Study of Regression and Classification Algorithms for Modelling Students' Academic Performance.. Educational Data Mining. 392–395. 10 indexed citations

14.

Cruz, Luís, et al.. (2015). A Comparative Study of Classification and Regression Algorithms for Modelling Students' Academic Performance.. Educational Data Mining. 57 indexed citations

15.

Appice, Annalisa, Pedro Pereira Rodrigues, Vı́tor Santos Costa, et al.. (2015). Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 7 indexed citations

16.

Pinto, Edgar, Carlos Soares, Cristina Couto, & Agostinho Almeida. (2015). Trace Elements in Ambient Air at Porto Metropolitan Area—Checking for Compliance with New European Union (Eu) Air Quality Standards. Journal of Toxicology and Environmental Health. 78(13-14). 848–859. 10 indexed citations

17.

Saleiro, Pedro, et al.. (2013). POPSTAR at RepLab 2013: Name ambiguity resolution on Twitter. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 8 indexed citations

18.

Sá, Cláudio Rebelo de, Carlos Soares, Alípio Jorge, Paulo J. Azevedo, & Joaquim Pinto da Costa. (2011). Mining association rules for label ranking. RepositóriUM (Universidade do Minho). 11 indexed citations

19.

Brazdil, Pavel, Christophe Giraud-Carrier, Carlos Soares, & Ricardo Vilalta. (2009). Metalearning - Applications to Data Mining. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 280 indexed citations

20.

Peng, Yonghong, Peter Flach, Carlos Soares, & Pavel Brazdil. (2002). Improved data set characterisation for meta-learning. Bristol Research (University of Bristol). 9 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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