Eva Maia
Impact in
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- Digital Transformation in Industry
- Flexible and Reconfigurable Manufacturing Systems
- Signal Processing top 5%
- Advanced Malware Detection Techniques
Papers in
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- Adversarial Robustness in Machine Learning 8
- Anomaly Detection Techniques and Applications 7
- Internet Traffic Analysis and Secure E-voting 6
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- Advanced Malware Detection Techniques 13
- Co-authors
- Isabel Praça (42 shared papers)Adrien Bécue (3 shared papers)Orlando Sousa (4 shared papers)João Augusto Nunes Vitorino (14 shared papers)Rogério Reis (8 shared papers)Nelma Moreira (8 shared papers)Ivone Amorim (8 shared papers)António José Marques (1 shared paper)
In The Last Decade
Eva Maia
43 papers receiving 479 citations
Peers
Comparison fields: 5 of 80
- Industrial and Manufacturing Engineering 127
- Signal Processing 113
- Computer Networks and Communications 210
- Artificial Intelligence 182
- Management Information Systems 27
Countries citing papers authored by Eva Maia
This map shows the geographic impact of Eva Maia'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 Eva Maia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eva Maia more than expected).
Fields of papers citing papers by Eva Maia
This network shows the impact of papers produced by Eva Maia. 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 Eva Maia. The network helps show where Eva Maia may publish in the future.
Co-authors
The 25 scholars most cited alongside Eva Maia, 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 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 149 | |
| 2 | 2021 | 95 | |
| 3 | 2023 | 32 | |
| 4 | 2023 | 31 | |
| 5 | 2022 | 30 | |
| 6 | 2023 | 26 | |
| 7 | 2020 | 20 | |
| 8 | 2022 | 11 | |
| 9 | 2025 | 11 | |
| 10 | 2023 | 9 | |
| 11 | 2019 | 9 | |
| 12 | 2024 | 6 | |
| 13 | 2015 | 5 | |
| 14 | 2022 | 5 | |
| 15 | 2022 | 5 | |
| 16 | 2023 | 4 | |
| 17 | 2022 | 4 | |
| 18 | 2015 | 4 | |
| 19 | 2017 | 4 | |
| 20 | 2020 | 4 |
About Eva Maia
Eva Maia is a scholar working on Artificial Intelligence, Signal Processing, Computer Networks and Communications, Computational Theory and Mathematics and Software, having authored 51 papers that have together received 503 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (17 papers), Advanced Malware Detection Techniques (13 papers), Adversarial Robustness in Machine Learning (8 papers), Anomaly Detection Techniques and Applications (7 papers), semigroups and automata theory (7 papers), Internet Traffic Analysis and Secure E-voting (6 papers), Digital Transformation in Industry (4 papers) and Flexible and Reconfigurable Manufacturing Systems (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (127 citations), Signal Processing (113 citations), Computer Networks and Communications (210 citations), Artificial Intelligence (182 citations) and Management Information Systems (27 citations). Eva Maia has collaborated with scholars based in Portugal, France and Germany. Frequent co-authors include Isabel Praça, Adrien Bécue, Orlando Sousa, João Augusto Nunes Vitorino, Rogério Reis, Nelma Moreira, Ivone Amorim, António José Marques, Artemisa R. Dores and Irene Palmares Carvalho. Their work appears in journals such as Applied Sciences, Information and Computation, Lecture notes in computer science, Computer Networks and Sensors.
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.