Raquel Sebastião
- Artificial Intelligence top 2%
- Computer Networks and Communications top 10%
- Signal Processing top 5%
- Information Systems top 10%
- Management Science and Operations Research top 10%
- Co-authors
- João GamaPedro Pereira RodriguesVítor SencadasTeresa MendonçaRaquel C. ConceiçãoMiguel Castelo‐BrancoRaquel FloresAldina Reis
- Topics
- Data Stream Mining Techniques (7 papers)EEG and Brain-Computer Interfaces (6 papers)Heart Rate Variability and Autonomic Control (6 papers)
In The Last Decade
Raquel Sebastião
27 papers receiving 735 citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 544
- Computer Networks and Communications 140
- Signal Processing 132
- Information Systems 90
- Management Science and Operations Research 70
Countries citing papers authored by Raquel Sebastião
This map shows the geographic impact of Raquel Sebastião'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 Raquel Sebastião with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raquel Sebastião more than expected).
Fields of papers citing papers by Raquel Sebastião
This network shows the impact of papers produced by Raquel Sebastião. 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 Raquel Sebastião. The network helps show where Raquel Sebastião may publish in the future.
Co-authorship network of co-authors of Raquel Sebastião
This figure shows the co-authorship network connecting the top 25 collaborators of Raquel Sebastião. A scholar is included among the top collaborators of Raquel Sebastião 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 Raquel Sebastião. Raquel Sebastião is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 33 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 23 | |
| 9 | 13 | |
| 10 | 4 | |
| 11 | 1 | |
| 12 | 6 | |
| 13 | 2 | |
| 14 | 2 | |
| 15 | 4 | |
| 16 | On evaluating stream learning algorithmsbreakdown → | 317 |
| 17 | 11 | |
| 18 | Drift Severity Metric | 6 |
| 19 | 23 | |
| 20 | 36 |
About Raquel Sebastião
Raquel Sebastião is a scholar working on Anesthesiology and Pain Medicine, Occupational Therapy and Cognitive Neuroscience, having authored 30 papers that have together received 761 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (7 papers), EEG and Brain-Computer Interfaces (6 papers) and Heart Rate Variability and Autonomic Control (6 papers). The work is most often cited by research in Artificial Intelligence (544 citations), Signal Processing (132 citations) and Developmental Neuroscience (31 citations). Raquel Sebastião has collaborated with scholars based in Portugal, Sweden and Spain. Frequent co-authors include João Gama, Pedro Pereira Rodrigues, Vítor Sencadas, Teresa Mendonça, Raquel C. Conceição, Miguel Castelo‐Branco, Raquel Flores, Aldina Reis, Jorge Saraiva and Rui Bernardes. Their work appears in journals such as Journal of Clinical Investigation, Advanced Functional Materials 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.