Zhili Pei

773 citations
30 papers · 497 indexed · h-index 9
Topics
Advanced Text Analysis Techniques (7 papers)Advanced Computational Techniques and Applications (5 papers)Text and Document Classification Technologies (5 papers)

In The Last Decade

Zhili Pei

29 papers receiving 480 citations

Peers

Zhili Pei
Comparison fields: 5 of 107
  • Artificial Intelligence 189
  • Molecular Biology 125
  • Computer Vision and Pattern Recognition 70
  • Information Systems 68
  • Organic Chemistry 66
Replace Fei Dai with:
Fei Dai China
V. Uma Maheswari India
Azah Kamilah Muda Malaysia
Nageswara Rao Moparthi India
Alexander Hall Switzerland
Suresh Dara India
Carlos Morell Cuba
Yenny Villuendas-Rey Mexico
Zhihua Hu China
Zhili Pei relative to Fei Dai China Fei Dai's profile →
Citations per field
00.5×10×20×27×
Fei Dai · 1×
Citations per year

Countries citing papers authored by Zhili Pei

Since Specialization
Citations

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

Fields of papers citing papers by Zhili Pei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhili Pei

This figure shows the co-authorship network connecting the top 25 collaborators of Zhili Pei. A scholar is included among the top collaborators of Zhili Pei 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 Zhili Pei. Zhili Pei 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 6
3 4
4 33
5 8
6 2
7 21
8 1
9 203
10 1
11
Robot Path Planning Method Based on Improved Genetic Algorithm
6
12 1
13 3
14 4
15 10
16 2
17 2
18 3
19 75
20 46

About Zhili Pei

Zhili Pei is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 30 papers that have together received 497 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (7 papers), Advanced Computational Techniques and Applications (5 papers) and Text and Document Classification Technologies (5 papers). The work is most often cited by research in Artificial Intelligence (189 citations), Computer Vision and Pattern Recognition (70 citations) and Information Systems (68 citations). Zhili Pei has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Mingyang Jiang, Yanchun Liang, Xiaojing Fan, Renchu Guan, Xiaoyue Feng, Yu Xue, Ravi Kurukulasuriya, Andrew J. Souers, J. T. Link and David J. Madar. Their work appears in journals such as SHILAP Revista de lepidopterología, International Journal of Molecular Sciences and Current Medicinal Chemistry.

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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