Xiaojun Ye

2.1k citations
150 papers · 1.2k · h-index 19

Impact in

Papers in

Xiaojun Ye

135 papers receiving 1.2k citations

Peers

Xiaojun Ye
Comparison fields: 5 of 150
  • Artificial Intelligence 280
  • Geriatrics and Gerontology 31
  • Statistical and Nonlinear Physics 90
  • Computer Vision and Pattern Recognition 144
  • Software 26
Replace Xiangjun Li with:
Xiangjun Li China
Qingxian Wang China
Shuhong Chen China
Zhicheng Cui United States
Saurav Mallik India
Qing Zhang China
Wenya Zhang China
Meng Liu China
Xiaojun Ye relative to Xiangjun Li China Xiangjun Li's profile →
Citations per field
00.5×20×40×54×
Xiangjun Li · 1×
Citations per year

Countries citing papers authored by Xiaojun Ye

Since Specialization
Citations

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

Fields of papers citing papers by Xiaojun Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaojun Ye, 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 Xiaojun Ye Line = papers co-authored together Xiaojun Ye links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 150 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201371
2 201768
3 201860
4 201756
5 202152
6 202251
7 202143
8 202038
9 202335
10 201832
11 202229
12 202027
13 201622
14 201921
15 201820
16 202019
17 201919
18 202219
19 201718
20 202118

About Xiaojun Ye

Xiaojun Ye is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Materials Chemistry, Information Systems and Computer Networks and Communications, having authored 150 papers that have together received 1.2k indexed citations. Recurring topics across this work include Silicon and Solar Cell Technologies (14 papers), Privacy-Preserving Technologies in Data (11 papers), 2D Materials and Applications (10 papers), Complex Network Analysis Techniques (9 papers), Internet Traffic Analysis and Secure E-voting (9 papers), Service-Oriented Architecture and Web Services (8 papers), Semiconductor materials and devices (8 papers) and Cryptography and Data Security (7 papers). The work is most often cited by research in Artificial Intelligence (280 citations), Geriatrics and Gerontology (31 citations), Statistical and Nonlinear Physics (90 citations), Computer Vision and Pattern Recognition (144 citations) and Software (26 citations). Xiaojun Ye has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Chaokun Wang, Hongbo Li, Rui Zhang, Zheng Wang, Jianmin Wang, Qiang Tu, Jing Yu, Xiao Yuan, Guiguang Ding and Hongbo Li. Their work appears in journals such as Journal of Materials Science Materials in Electronics, Materials Science in Semiconductor Processing, Journal of Physics and Chemistry of Solids, Tsinghua Science & Technology and RSC Advances.

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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