Xiaohong Wang

1.2k citations
64 papers · 981 · h-index 15

Impact in

Papers in

Xiaohong Wang

57 papers receiving 956 citations

Peers

Xiaohong Wang
Comparison fields: 5 of 78
  • Computer Networks and Communications 291
  • Automotive Engineering 106
  • Statistical and Nonlinear Physics 67
  • Control and Systems Engineering 119
  • Modeling and Simulation 22
Replace Aleksey A. Kudreyko with:
Aleksey A. Kudreyko Russia
Xu Cheng China
G.S. Tombras Greece
Bruce R. Davis Australia
Ezzat G. Bakhoum United States
Khalid Hamed Alharbi Saudi Arabia
Xiaoping Xie China
Jingjun Zhang China
Kirsten Morris Canada
Denis Navarro Spain
Xiaohong Wang relative to Aleksey A. Kudreyko Russia Aleksey A. Kudreyko's profile →
Citations per field
00.5×2×4×6×8×9.6×
Aleksey A. Kudreyko · 1×
Citations per year

Countries citing papers authored by Xiaohong Wang

Since Specialization
Citations

This map shows the geographic impact of Xiaohong Wang'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 Xiaohong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaohong Wang more than expected).

Fields of papers citing papers by Xiaohong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaohong Wang. 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 Xiaohong Wang. The network helps show where Xiaohong Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Xiaohong Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaohong Wang Line = papers co-authored together Xiaohong Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017193
2 2009118
3 201475
4 201472
5 201040
6 201740
7 201339
8 200837
9 201530
10 201429
11 201725
12 200524
13 200721
14 201720
15 201318
16 201215
17 199913
18 200312
19 201812
20 201511

About Xiaohong Wang

Xiaohong Wang is a scholar working on Computer Networks and Communications, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Artificial Intelligence and Automotive Engineering, having authored 64 papers that have together received 981 indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (15 papers), Quantum Information and Cryptography (8 papers), Advanced Mathematical Modeling in Engineering (5 papers), Advanced Chemical Physics Studies (4 papers), Reservoir Engineering and Simulation Methods (4 papers), Chaos control and synchronization (3 papers), Advanced Numerical Methods in Computational Mathematics (3 papers) and Color Science and Applications (3 papers). The work is most often cited by research in Computer Networks and Communications (291 citations), Automotive Engineering (106 citations), Statistical and Nonlinear Physics (67 citations), Control and Systems Engineering (119 citations) and Modeling and Simulation (22 citations). Xiaohong Wang has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Minghui Jiang, Zhen Wang, Xia Huang, Yuxia Li, Jun Mei, Joel M. Bowman, Zhou Wu, Jiexin Pu, Zhuo Xiong and Rendong Wu. Their work appears in journals such as Optik, Journal of Computational Physics, Nonlinear Dynamics, Numerical Methods for Partial Differential Equations and The Visual Computer.

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.

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