Gérard Dray
Impact in
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces
- Neural and Behavioral Psychology Studies
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- Transcranial Magnetic Stimulation Studies
Papers in
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- Advanced Text Analysis Techniques 9
- Natural Language Processing Techniques 6
- Topic Modeling 5
- Sentiment Analysis and Opinion Mining 5
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- EEG and Brain-Computer Interfaces 8
- Functional Brain Connectivity Studies 4
- Co-authors
- D.W. Pearson (7 shared papers)Stéphane Perrey (21 shared papers)Gérard Derosière (5 shared papers)Pascal Poncelet (14 shared papers)Kévin Mandrick (3 shared papers)Mathieu Roche (10 shared papers)Tomás Ward (3 shared papers)Jean‐Paul Micallef (2 shared papers)
In The Last Decade
Gérard Dray
46 papers receiving 579 citations
Peers
Comparison fields: 5 of 106
- Cognitive Neuroscience 127
- Neurology 44
- Radiology, Nuclear Medicine and Imaging 116
- Artificial Intelligence 177
- Information Systems 91
Countries citing papers authored by Gérard Dray
This map shows the geographic impact of Gérard Dray'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 Gérard Dray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gérard Dray more than expected).
Fields of papers citing papers by Gérard Dray
This network shows the impact of papers produced by Gérard Dray. 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 Gérard Dray. The network helps show where Gérard Dray may publish in the future.
Co-authors
The 25 scholars most cited alongside Gérard Dray, 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 | 1998 | 87 | |
| 2 | 2013 | 80 | |
| 3 | 2008 | 69 | |
| 4 | 2013 | 48 | |
| 5 | 2014 | 47 | |
| 6 | 2019 | 31 | |
| 7 | 2013 | 27 | |
| 8 | Web Analyzing Traffic Challenge: Description and Results | 2007 | 26 |
| 9 | 2000 | 21 | |
| 10 | 2021 | 15 | |
| 11 | 2001 | 14 | |
| 12 | 2005 | 14 | |
| 13 | 2008 | 13 | |
| 14 | 2023 | 11 | |
| 15 | 2004 | 10 | |
| 16 | Opinion Mining From Blogs | 2009 | 9 |
| 17 | 2023 | 9 | |
| 18 | 2011 | 8 | |
| 19 | 2024 | 7 | |
| 20 | 2022 | 6 |
About Gérard Dray
Gérard Dray is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Information Systems, Biomedical Engineering and Computer Vision and Pattern Recognition, having authored 55 papers that have together received 625 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (9 papers), EEG and Brain-Computer Interfaces (8 papers), Natural Language Processing Techniques (6 papers), Web Data Mining and Analysis (6 papers), Optical Imaging and Spectroscopy Techniques (5 papers), Topic Modeling (5 papers), Sentiment Analysis and Opinion Mining (5 papers) and Functional Brain Connectivity Studies (4 papers). The work is most often cited by research in Cognitive Neuroscience (127 citations), Neurology (44 citations), Radiology, Nuclear Medicine and Imaging (116 citations), Artificial Intelligence (177 citations) and Information Systems (91 citations). Gérard Dray has collaborated with scholars based in France, Ireland and Albania. Frequent co-authors include D.W. Pearson, Stéphane Perrey, Gérard Derosière, Pascal Poncelet, Kévin Mandrick, Mathieu Roche, Tomás Ward, Jean‐Paul Micallef, Jacky Montmain and Makii Muthalib. Their work appears in journals such as Frontiers in Human Neuroscience, Applied Network Science, Journal of Diabetes Science and Technology, Mathematical and Computer Modelling and IEEE Software.
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.