Lili Zhou

1.6k citations
63 papers · 1.2k indexed · h-index 19
Topics
Neural Networks Stability and Synchronization (31 papers)Nonlinear Dynamics and Pattern Formation (25 papers)Chaos control and synchronization (14 papers)

In The Last Decade

Lili Zhou

59 papers receiving 1.2k citations

Peers

Lili Zhou
Comparison fields: 5 of 71
  • Statistical and Nonlinear Physics 749
  • Computer Networks and Communications 680
  • Electrical and Electronic Engineering 312
  • Computer Vision and Pattern Recognition 273
  • Artificial Intelligence 124
Replace Gervais Dolvis Leutcho with:
Gervais Dolvis Leutcho Cameroon
Qiuzhen Wan China
Xinlei An China
Xinxin Kong China
Tengfei Lei China
Théophile Fonzin Fozin Cameroon
Jay Prakash Singh India
I. Μ. Kyprianidis Greece
Quanli Deng China
Victor Kamdoum Tamba Cameroon
Lili Zhou relative to Gervais Dolvis Leutcho Cameroon Gervais Dolvis Leutcho's profile →
Citations per field
00.5×10×13.7×
Gervais Dolvis Leutcho · 1×
Citations per year

Countries citing papers authored by Lili Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Lili Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lili Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Lili Zhou. A scholar is included among the top collaborators of Lili Zhou 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 Lili Zhou. Lili Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 7
5 9
6 1
7 5
8 3
9 3
10 23
11 4
12 1
13 14
14 30
15 21
16 41
17 12
18 79
19 14
20 2

About Lili Zhou

Lili Zhou is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 63 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (31 papers), Nonlinear Dynamics and Pattern Formation (25 papers) and Chaos control and synchronization (14 papers). The work is most often cited by research in Statistical and Nonlinear Physics (749 citations), Computer Networks and Communications (680 citations) and Computer Vision and Pattern Recognition (273 citations). Lili Zhou has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Fei Tan, Chunhua Wang, Zhou Ling, Fei Yu, Wei Liu, Junwei Lu, Sichun Du, Yu‐Ming Chu, Yongmin Li and Yuan Lin. Their work appears in journals such as Advanced Materials, Nano Letters and ACS Nano.

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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