Quanying Liu
- Cognitive Neuroscience top 2%
- Biomedical Engineering top 5%
- Molecular Biology
- Atomic and Molecular Physics, and Optics top 10%
- Materials Chemistry
- Co-authors
- Dante MantiniNicole WenderothRichard J. BushbySøren Møller PedersenAhmed H. ZewailJennifer L. HerekN. BodenCamillo Porcaro
- Topics
- EEG and Brain-Computer Interfaces (37 papers)Neural dynamics and brain function (27 papers)Functional Brain Connectivity Studies (27 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Quanying Liu
117 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Cognitive Neuroscience 923
- Biomedical Engineering 625
- Molecular Biology 307
- Atomic and Molecular Physics, and Optics 260
- Materials Chemistry 251
Countries citing papers authored by Quanying Liu
This map shows the geographic impact of Quanying Liu'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 Quanying Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quanying Liu more than expected).
Fields of papers citing papers by Quanying Liu
This network shows the impact of papers produced by Quanying Liu. 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 Quanying Liu. The network helps show where Quanying Liu may publish in the future.
Co-authorship network of co-authors of Quanying Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Quanying Liu. A scholar is included among the top collaborators of Quanying Liu 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 Quanying Liu. Quanying Liu 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 | 5 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | Injectable Microgels with Hybrid Exosomes of Chondrocyte‐Targeted FGF18 Gene‐Editing and Self‐Renewable Lubrication for Osteoarthritis Therapybreakdown → | 96 |
| 10 | 4 | |
| 11 | 7 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 35 | |
| 15 | 1 | |
| 16 | 13 | |
| 17 | 1 | |
| 18 | 39 | |
| 19 | 45 | |
| 20 | 56 |
About Quanying Liu
Quanying Liu is a scholar working on Cognitive Neuroscience, Computational Mathematics and Neurology, having authored 124 papers that have together received 2.5k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (37 papers), Neural dynamics and brain function (27 papers) and Functional Brain Connectivity Studies (27 papers). The work is most often cited by research in Cognitive Neuroscience (923 citations), Biomedical Engineering (625 citations) and Computational Mathematics (8 citations). Quanying Liu has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Dante Mantini, Nicole Wenderoth, Richard J. Bushby, Søren Møller Pedersen, Ahmed H. Zewail, Jennifer L. Herek, N. Boden, Camillo Porcaro, Yujiang Fan and Jie Liang. Their work appears in journals such as Nature, Advanced Materials and Angewandte Chemie International Edition.
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.