Joan Liu‐Shuang
- Cognitive Neuroscience top 2%
- Experimental and Cognitive Psychology top 5%
- Computer Vision and Pattern Recognition top 5%
- Social Psychology
- Developmental and Educational Psychology
- Co-authors
- Bruno RossionAnthony M. NorciaKatrien TorfsCorentin JacquesMeike RamonTalia L. RetterGoedele Van BelleLuca Vizioli
- Topics
- Face Recognition and Perception (19 papers)Visual perception and processing mechanisms (12 papers)Neural dynamics and brain function (9 papers)
- Cited by
- Cognitive NeuroscienceExperimental and Cognitive PsychologyComputer Vision and Pattern Recognition
- Partner nations
- BelgiumFranceUnited States
In The Last Decade
Joan Liu‐Shuang
20 papers receiving 878 citations
Peers
Comparison fields: 5 of 39
- Cognitive Neuroscience 851
- Experimental and Cognitive Psychology 262
- Computer Vision and Pattern Recognition 157
- Social Psychology 77
- Developmental and Educational Psychology 45
Countries citing papers authored by Joan Liu‐Shuang
This map shows the geographic impact of Joan Liu‐Shuang'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 Joan Liu‐Shuang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joan Liu‐Shuang more than expected).
Fields of papers citing papers by Joan Liu‐Shuang
This network shows the impact of papers produced by Joan Liu‐Shuang. 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 Joan Liu‐Shuang. The network helps show where Joan Liu‐Shuang may publish in the future.
Co-authorship network of co-authors of Joan Liu‐Shuang
This figure shows the co-authorship network connecting the top 25 collaborators of Joan Liu‐Shuang. A scholar is included among the top collaborators of Joan Liu‐Shuang 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 Joan Liu‐Shuang. Joan Liu‐Shuang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 3 | |
| 3 | 60 | |
| 4 | 16 | |
| 5 | 20 | |
| 6 | 1 | |
| 7 | 23 | |
| 8 | 22 | |
| 9 | 1 | |
| 10 | 23 | |
| 11 | 43 | |
| 12 | 107 | |
| 13 | 70 | |
| 14 | 140 | |
| 15 | 12 | |
| 16 | 19 | |
| 17 | 1 | |
| 18 | 67 | |
| 19 | 86 | |
| 20 | 171 |
About Joan Liu‐Shuang
Joan Liu‐Shuang is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 889 indexed citations. Recurring topics across this work include Face Recognition and Perception (19 papers), Visual perception and processing mechanisms (12 papers) and Neural dynamics and brain function (9 papers). The work is most often cited by research in Cognitive Neuroscience (851 citations), Experimental and Cognitive Psychology (262 citations) and Computer Vision and Pattern Recognition (157 citations). Joan Liu‐Shuang has collaborated with scholars based in Belgium, France and United States. Frequent co-authors include Bruno Rossion, Anthony M. Norcia, Katrien Torfs, Corentin Jacques, Meike Ramon, Talia L. Retter, Goedele Van Belle, Luca Vizioli, Louis Maillard and Jacques Jonas. Their work appears in journals such as Proceedings of the National Academy of Sciences, NeuroImage and Neuropsychologia.
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.