Paula Branco
Impact in
- Artificial Intelligence top 2%
- Imbalanced Data Classification Techniques
- Anomaly Detection Techniques and Applications
- Machine Learning and Data Classification
- Data Stream Mining Techniques
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- Artificial Intelligence in Healthcare
Papers in
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- Imbalanced Data Classification Techniques 21
- Anomaly Detection Techniques and Applications 14
- Machine Learning and Data Classification 7
- Machine Learning and Algorithms 4
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- Network Security and Intrusion Detection 12
- Co-authors
- Luı́s Torgo (20 shared papers)Rita P. Ribeiro (8 shared papers)Nuno Moniz (6 shared papers)Bernhard Pfahringer (2 shared papers)Nathalie Japkowicz (4 shared papers)Kushankur Ghosh (1 shared paper)Colin Bellinger (3 shared papers)Bartosz Krawczyk (3 shared papers)
- Journals
- ACM Computing Surveys (3 papers)Machine Learning (3 papers)Applied Intelligence (2 papers)Natural Language Engineering (2 papers)IEEE Access (2 papers)
- Partner nations
- CanadaPortugalUnited States
In The Last Decade
Paula Branco
51 papers receiving 1.4k citations
Paula Branco's Hit Papers
Peers
Comparison fields: 5 of 162
- Artificial Intelligence 725
- Health Information Management 67
- Signal Processing 119
- Software 26
- Information Systems 136
Countries citing papers authored by Paula Branco
This map shows the geographic impact of Paula Branco'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 Paula Branco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paula Branco more than expected).
Fields of papers citing papers by Paula Branco
This network shows the impact of papers produced by Paula Branco. 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 Paula Branco. The network helps show where Paula Branco may publish in the future.
Co-authors
The 25 scholars most cited alongside Paula Branco, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Survey of Predictive Modeling on Imbalanced Domains Hit paper breakdown → | 2016 | 753 |
| 2 | 2022 | 125 | |
| 3 | 2014 | 105 | |
| 4 | SMOGN: a Pre-processing Approach for Imbalanced Regression | 2017 | 95 |
| 5 | 2019 | 73 | |
| 6 | 2017 | 49 | |
| 7 | 2024 | 35 | |
| 8 | 2016 | 19 | |
| 9 | 2024 | 13 | |
| 10 | 2024 | 13 | |
| 11 | 2022 | 12 | |
| 12 | REBAGG: REsampled BAGGing for Imbalanced Regression | 2018 | 11 |
| 13 | 2023 | 11 | |
| 14 | Evaluation of Ensemble Methods in Imbalanced Regression Tasks | 2017 | 10 |
| 15 | 2024 | 10 | |
| 16 | 2017 | 10 | |
| 17 | 2023 | 8 | |
| 18 | 2023 | 8 | |
| 19 | 2023 | 8 | |
| 20 | 2024 | 8 |
About Paula Branco
Paula Branco is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Information Systems and Management Science and Operations Research, having authored 55 papers that have together received 1.5k indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (21 papers), Anomaly Detection Techniques and Applications (14 papers), Network Security and Intrusion Detection (12 papers), Advanced Malware Detection Techniques (9 papers), Machine Learning and Data Classification (7 papers), Spam and Phishing Detection (6 papers), Machine Learning and Algorithms (4 papers) and Misinformation and Its Impacts (4 papers). The work is most often cited by research in Artificial Intelligence (725 citations), Health Information Management (67 citations), Signal Processing (119 citations), Software (26 citations) and Information Systems (136 citations). Paula Branco has collaborated with scholars based in Canada, Portugal and United States. Frequent co-authors include Luı́s Torgo, Rita P. Ribeiro, Nuno Moniz, Bernhard Pfahringer, Nathalie Japkowicz, Kushankur Ghosh, Colin Bellinger, Bartosz Krawczyk, Roberto Corizzo and Guy-Vincent Jourdan. Their work appears in journals such as ACM Computing Surveys, Machine Learning, Applied Intelligence, Natural Language Engineering and IEEE Access.
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.