Suyu Liu
- Statistical and Nonlinear Physics top 5%
- Computer Networks and Communications top 10%
- Modeling and Simulation top 5%
- Cognitive Neuroscience
- Cellular and Molecular Neuroscience
- Co-authors
- Nicola PerraMárton KarsaiAlessandro VespignaniWeigang SunQingyun WangDenggui FanYifan LiAmol J. Ghia
- Topics
- Complex Network Analysis Techniques (7 papers)Neural dynamics and brain function (3 papers)Opinion Dynamics and Social Influence (3 papers)
- Cited by
- Statistical and Nonlinear PhysicsModeling and SimulationComputer Networks and Communications
- Journals
- Physical Review LettersThe EMBO JournalInternational Journal of Radiation Oncology*Biology*Physics
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Suyu Liu
15 papers receiving 256 citations
Peers
Comparison fields: 5 of 63
- Statistical and Nonlinear Physics 175
- Computer Networks and Communications 62
- Modeling and Simulation 45
- Cognitive Neuroscience 44
- Cellular and Molecular Neuroscience 31
Countries citing papers authored by Suyu Liu
This map shows the geographic impact of Suyu 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 Suyu Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suyu Liu more than expected).
Fields of papers citing papers by Suyu Liu
This network shows the impact of papers produced by Suyu 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 Suyu Liu. The network helps show where Suyu Liu may publish in the future.
Co-authorship network of co-authors of Suyu Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Suyu Liu. A scholar is included among the top collaborators of Suyu 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 Suyu Liu. Suyu 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 | 1 | |
| 2 | 4 | |
| 3 | 12 | |
| 4 | 9 | |
| 5 | 18 | |
| 6 | 21 | |
| 7 | 27 | |
| 8 | 1 | |
| 9 | 18 | |
| 10 | 2 | |
| 11 | 21 | |
| 12 | 124 | |
| 13 | Controlling Contagion Processes in Time-Varying Networks | 4 |
| 14 | 1 | |
| 15 | 3 |
About Suyu Liu
Suyu Liu is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Condensed Matter Physics, having authored 15 papers that have together received 266 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (7 papers), Neural dynamics and brain function (3 papers) and Opinion Dynamics and Social Influence (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (175 citations), Modeling and Simulation (45 citations) and Computer Networks and Communications (62 citations). Suyu Liu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Nicola Perra, Márton Karsai, Alessandro Vespignani, Weigang Sun, Qingyun Wang, Denggui Fan, Yifan Li, Amol J. Ghia, Tharakeswara Bathala and B. Ashleigh Guadagnolo. Their work appears in journals such as Physical Review Letters, The EMBO Journal and International Journal of Radiation Oncology*Biology*Physics.
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.