Rita P. Ribeiro

3.0k total citations · 1 hit paper
33 papers, 1.3k citations indexed

About

Rita P. Ribeiro is a scholar working on Artificial Intelligence, Control and Systems Engineering and Health Information Management. According to data from OpenAlex, Rita P. Ribeiro has authored 33 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 6 papers in Control and Systems Engineering and 4 papers in Health Information Management. Recurrent topics in Rita P. Ribeiro's work include Imbalanced Data Classification Techniques (13 papers), Anomaly Detection Techniques and Applications (9 papers) and Machine Learning and Data Classification (8 papers). Rita P. Ribeiro is often cited by papers focused on Imbalanced Data Classification Techniques (13 papers), Anomaly Detection Techniques and Applications (9 papers) and Machine Learning and Data Classification (8 papers). Rita P. Ribeiro collaborates with scholars based in Portugal, United States and New Zealand. Rita P. Ribeiro's co-authors include Luı́s Torgo, Paula Branco, Nuno Moniz, João Gama, Pedro Pereira, Bernhard Pfahringer, Bruno Veloso, Narjes Davari, Nitesh V. Chawla and Vítor Cerqueira and has published in prestigious journals such as Cancer, Sensors and ACM Computing Surveys.

In The Last Decade

Rita P. Ribeiro

30 papers receiving 1.3k citations

Hit Papers

A Survey of Predictive Modeling on Imbalanced Domains 2016 2026 2019 2022 2016 200 400 600
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.

  1. A Survey of Predictive Modeling on Imbalanced Domains
    2016 738 citations Paula Branco, Luı́s Torgo et al. ACM Computing Surveys profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rita P. Ribeiro Portugal 14 679 195 104 96 95 33 1.3k
Dalwinder Singh India 10 420 0.6× 135 0.7× 80 0.8× 87 0.9× 164 1.7× 21 1.4k
Amel Ali Alhussan Saudi Arabia 24 536 0.8× 227 1.2× 95 0.9× 74 0.8× 201 2.1× 120 1.5k
Dong Xibin China 3 467 0.7× 131 0.7× 75 0.7× 82 0.9× 159 1.7× 8 1.3k
Hang Lei China 11 370 0.5× 162 0.8× 87 0.8× 114 1.2× 153 1.6× 68 1.4k
Ibomoiye Domor Mienye South Africa 22 1.0k 1.5× 228 1.2× 66 0.6× 156 1.6× 126 1.3× 41 2.2k
Hany F. ElYamany Egypt 7 422 0.6× 291 1.5× 93 0.9× 122 1.3× 86 0.9× 15 1.1k
Abiodun M. Ikotun South Africa 9 570 0.8× 171 0.9× 81 0.8× 157 1.6× 239 2.5× 20 1.6k
Paula Branco Canada 12 705 1.0× 199 1.0× 41 0.4× 132 1.4× 111 1.2× 55 1.4k
Liyong Zhang China 19 431 0.6× 126 0.6× 98 0.9× 104 1.1× 145 1.5× 125 1.0k
Lars Kotthoff United States 11 859 1.3× 142 0.7× 72 0.7× 153 1.6× 154 1.6× 50 1.9k

Countries citing papers authored by Rita P. Ribeiro

Since Specialization
Citations

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

Fields of papers citing papers by Rita P. Ribeiro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rita P. Ribeiro. 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 Rita P. Ribeiro. The network helps show where Rita P. Ribeiro may publish in the future.

Co-authorship network of co-authors of Rita P. Ribeiro

This figure shows the co-authorship network connecting the top 25 collaborators of Rita P. Ribeiro. A scholar is included among the top collaborators of Rita P. Ribeiro 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 Rita P. Ribeiro. Rita P. Ribeiro 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.
Ribeiro, Rita P., et al.. (2026). A systematic review on wearable-enabled remote health monitoring. Digital Health. 12. 620072099–620072099.
2.
Chandramohan, M., et al.. (2025). Screening Urban Soil Contamination in Rome: Insights from XRF and Multivariate Analysis. Environments. 12(4). 126–126.
3.
Ribeiro, Rita P., et al.. (2025). Histogram approaches for imbalanced data streams regression. Machine Learning. 114(12). 1 indexed citations
4.
Nunes, Tiago, et al.. (2024). Orofacial assessment as digital path for forensic and legal evidence record. Forensic Sciences Research. 9(3). owae006–owae006. 2 indexed citations
5.
Côrte-Real, Ana, et al.. (2024). Digital intraoral and radiologic records in forensic identification: Match with disruptive technology. Forensic Science International. 361. 112104–112104. 4 indexed citations
6.
Summavielle, Teresa, et al.. (2023). Multimodal Classification of Anxiety Based on Physiological Signals. Applied Sciences. 13(11). 6368–6368. 13 indexed citations
7.
Ribeiro, Rita P., et al.. (2023). An Online Anomaly Detection Approach for Fault Detection on Fire Alarm Systems. Sensors. 23(10). 4902–4902. 6 indexed citations
8.
Gama, João, Sławomir Nowaczyk, Sepideh Pashami, et al.. (2023). XAI for Predictive Maintenance. 5798–5799. 4 indexed citations
9.
Veloso, Bruno, Rita P. Ribeiro, João Gama, & Pedro Pereira. (2022). The MetroPT dataset for predictive maintenance. Scientific Data. 9(1). 764–764. 19 indexed citations
10.
Gama, João, Concha Bielza, Salvador García, et al.. (2021). DSAA 2021. IEEE Computational Intelligence Magazine. 16(2). C3–C3. 1 indexed citations
11.
Ribeiro, Rita P., et al.. (2021). Latex membranes with methylene blue dye for antimicrobial photodynamic therapy. Photochemical & Photobiological Sciences. 20(8). 1027–1032. 2 indexed citations
12.
Davari, Narjes, Bruno Veloso, Rita P. Ribeiro, Pedro Pereira, & João Gama. (2021). Predictive maintenance based on anomaly detection using deep learning for air production unit in the railway industry. 1–10. 24 indexed citations
13.
Ribeiro, Rita P., et al.. (2020). Using Property-Based Testing to Generate Feedback for C Programming Exercises. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 1 indexed citations
14.
Branco, Paula, Luı́s Torgo, & Rita P. Ribeiro. (2018). REBAGG: REsampled BAGGing for Imbalanced Regression. 67–81. 11 indexed citations
15.
Branco, Paula, Luı́s Torgo, & Rita P. Ribeiro. (2018). Resampling with neighbourhood bias on imbalanced domains. Expert Systems. 35(4). 4 indexed citations
16.
Branco, Paula, Luı́s Torgo, & Rita P. Ribeiro. (2017). SMOGN: a Pre-processing Approach for Imbalanced Regression. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 36–50. 90 indexed citations
17.
Branco, Paula, Luı́s Torgo, Rita P. Ribeiro, et al.. (2017). Learning Through Utility Optimization in Regression Tasks. Research Commons (University of Waikato). 2. 30–39. 3 indexed citations
18.
Branco, Paula, Luı́s Torgo, & Rita P. Ribeiro. (2016). A Survey of Predictive Modeling on Imbalanced Domains. ACM Computing Surveys. 49(2). 1–50. 738 indexed citations breakdown →
19.
Loureiro, D., et al.. (2014). Innovative smart metering based applications for water utilities. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 1 indexed citations
20.
Ribeiro, Rita P., et al.. (2008). Utility-based Performance Measures for Regression. Cancer. 22(3). 533–44. 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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