Cong Li

1.4k citations
105 papers · 1.0k · h-index 15

Impact in

Papers in

Cong Li

94 papers receiving 972 citations

Peers

Cong Li
Comparison fields: 5 of 109
  • Computer Networks and Communications 260
  • Artificial Intelligence 306
  • Biomaterials 92
  • Hardware and Architecture 44
  • Computer Vision and Pattern Recognition 122
Replace Bin Xing with:
Bin Xing China
Juan Antonio Holgado-Terriza Spain
Yufei Jiang China
Lei Feng Sweden
Amritpal Singh India
Zhiyi Huang New Zealand
Mohd Asif Shah India
Guohui Wang United States
Kyungtae Kang South Korea
Chunming Tang China
Cong Li relative to Bin Xing China Bin Xing's profile →
Citations per field
00.5×1.5×2×2.5×
Bin Xing · 1×
Citations per year

Countries citing papers authored by Cong Li

Since Specialization
Citations

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

Fields of papers citing papers by Cong Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016118
2 201996
3 200451
4 201450
5 202447
6 200933
7 200125
8 201824
9 201821
10 202020
11 201020
12 201119
13 201419
14 202217
15 202416
16 201915
17 201815
18 201315
19 202115
20 201615

About Cong Li

Cong Li is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 105 papers that have together received 1.0k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (12 papers), Advanced Data Storage Technologies (9 papers), Recommender Systems and Techniques (7 papers), Parallel Computing and Optimization Techniques (7 papers), Face and Expression Recognition (6 papers), Anomaly Detection Techniques and Applications (5 papers), Topic Modeling (5 papers) and Cooperative Communication and Network Coding (5 papers). The work is most often cited by research in Computer Networks and Communications (260 citations), Artificial Intelligence (306 citations), Biomaterials (92 citations), Hardware and Architecture (44 citations) and Computer Vision and Pattern Recognition (122 citations). Cong Li has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Hang Li, Haibin Duan, Wenhang Wang, Yunduo Long, Yonghao Ni, Hongjie Zhang, Xiaofei Wang, Huan Zhou, Tong Han and Hui Juan Zhao. Their work appears in journals such as Wireless Communications and Mobile Computing, Applied Soft Computing, IEEE Intelligent Systems, IEEE Transactions on Magnetics and Results in Engineering.

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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