Ying Xie
- Cognitive Neuroscience top 5%
- Statistical and Nonlinear Physics top 1%
- Electrical and Electronic Engineering
- Computer Networks and Communications top 5%
- Cellular and Molecular Neuroscience top 10%
- Topics
- Neural dynamics and brain function (25 papers)stochastic dynamics and bifurcation (22 papers)Nonlinear Dynamics and Pattern Formation (14 papers)
- Cited by
- Statistical and Nonlinear PhysicsCognitive NeuroscienceComputer Networks and Communications
- Partner nations
- ChinaUnited States
In The Last Decade
Ying Xie
36 papers receiving 749 citations
Hit Papers
Peers
Comparison fields: 5 of 45
- Cognitive Neuroscience 568
- Statistical and Nonlinear Physics 547
- Electrical and Electronic Engineering 285
- Computer Networks and Communications 227
- Cellular and Molecular Neuroscience 172
Countries citing papers authored by Ying Xie
This map shows the geographic impact of Ying Xie'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 Ying Xie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Xie more than expected).
Fields of papers citing papers by Ying Xie
This network shows the impact of papers produced by Ying Xie. 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 Ying Xie. The network helps show where Ying Xie may publish in the future.
Co-authorship network of co-authors of Ying Xie
This figure shows the co-authorship network connecting the top 25 collaborators of Ying Xie. A scholar is included among the top collaborators of Ying Xie 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 Ying Xie. Ying Xie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 8 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 25 | |
| 7 | A biophysical neuron model with double membranesbreakdown → | 47 |
| 8 | 31 | |
| 9 | 1 | |
| 10 | A novel memristive neuron model and its energy characteristicsbreakdown → | 48 |
| 11 | 32 | |
| 12 | 16 | |
| 13 | 32 | |
| 14 | 31 | |
| 15 | 25 | |
| 16 | 68 | |
| 17 | 29 | |
| 18 | 16 | |
| 19 | 93 | |
| 20 | Economy and reliability analysis of connection modes in urban distribution networks | 2 |
About Ying Xie
Ying Xie is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Computer Networks and Communications, having authored 37 papers that have together received 755 indexed citations. Recurring topics across this work include Neural dynamics and brain function (25 papers), stochastic dynamics and bifurcation (22 papers) and Nonlinear Dynamics and Pattern Formation (14 papers). The work is most often cited by research in Statistical and Nonlinear Physics (547 citations), Cognitive Neuroscience (568 citations) and Computer Networks and Communications (227 citations). Ying Xie has collaborated with scholars based in China and United States. Frequent co-authors include Jun Ma, Zhao Yao, Ya Jia, Yitong Guo, Xikui Hu, Yanni Li, Yonghong Wu, Qianming Ding, Xuening Li and Ying Xu. Their work appears in journals such as Physics Letters A, Neural Networks and Physica D Nonlinear Phenomena.
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.