Pinghui Wang

1.7k citations
103 papers · 1.0k · h-index 16

Impact in

Papers in

Pinghui Wang

93 papers receiving 1.0k citations

Peers

Pinghui Wang
Comparison fields: 5 of 89
  • Statistical and Nonlinear Physics 248
  • Artificial Intelligence 520
  • Computer Networks and Communications 293
  • Transportation 72
  • Signal Processing 111
Replace Kun Kuang with:
Kun Kuang China
Shuhan Yuan United States
Amogh Dhamdhere United States
Ruizhang Huang China
Ulrich Meyer Germany
Hasan Davulcu United States
Tossapon Boongoen Thailand
Kaize Ding United States
Peiquan Jin China
Yixin Liu China
Pinghui Wang relative to Kun Kuang China Kun Kuang's profile →
Citations per field
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Kun Kuang · 1×
Citations per year

Countries citing papers authored by Pinghui Wang

Since Specialization
Citations

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

Fields of papers citing papers by Pinghui Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020109
2 202383
3 201463
4 201648
5 202138
6 201732
7 201031
8 202228
9 201425
10 201623
11 202420
12 201120
13 201918
14 201018
15 201816
16 201915
17 201715
18 202315
19 202115
20 202114

About Pinghui Wang

Pinghui Wang is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition, having authored 103 papers that have together received 1.0k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (30 papers), Advanced Graph Neural Networks (25 papers), Network Security and Intrusion Detection (14 papers), Internet Traffic Analysis and Secure E-voting (12 papers), Data Management and Algorithms (8 papers), Topic Modeling (8 papers), Caching and Content Delivery (8 papers) and Human Mobility and Location-Based Analysis (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (248 citations), Artificial Intelligence (520 citations), Computer Networks and Communications (293 citations), Transportation (72 citations) and Signal Processing (111 citations). Pinghui Wang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Xiaohong Guan, Junzhou Zhao, John C. S. Lui, Jing Tao, Don Towsley, Nuo Xu, Tao Qin, Li Pan, Long Chen and Xiaoyan Wang. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Information Sciences, ACM Transactions on Knowledge Discovery from Data, Knowledge and Information Systems and Knowledge-Based Systems.

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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