Pinghui Wang

430 citations
25 papers · 233 · h-index 7

Impact in

Papers in

    • Internet Traffic Analysis and Secure E-voting 6
    • Advanced Graph Neural Networks 4
    • Anomaly Detection Techniques and Applications 3
    • Topic Modeling 3
    • Natural Language Processing Techniques 2
    • Network Security and Intrusion Detection 5
    • Caching and Content Delivery 2

Pinghui Wang

22 papers receiving 232 citations

Peers

Pinghui Wang
Comparison fields: 5 of 39
  • Statistical and Nonlinear Physics 93
  • Computer Networks and Communications 119
  • Artificial Intelligence 141
  • Hardware and Architecture 17
  • Signal Processing 27
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Citations per field
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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 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201255
2 201142
3 201738
4 201323
5 201417
6 200914
7 202312
8 20184
9 20184
10 20254
11 20243
12 20242
13 20242
14 20182
15 20242
16 20242
17 20242
18 20231
19
Risk Decision Making of Science and Technology Project Based on Interval Bayesian Model
20121
20 20251

About Pinghui Wang

Pinghui Wang is a scholar working on Artificial Intelligence, Computer Networks and Communications, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition and Political Science and International Relations, having authored 25 papers that have together received 233 indexed citations. Recurring topics across this work include Internet Traffic Analysis and Secure E-voting (6 papers), Network Security and Intrusion Detection (5 papers), Advanced Graph Neural Networks (4 papers), Complex Network Analysis Techniques (4 papers), Anomaly Detection Techniques and Applications (3 papers), Topic Modeling (3 papers), Natural Language Processing Techniques (2 papers) and Caching and Content Delivery (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (93 citations), Computer Networks and Communications (119 citations), Artificial Intelligence (141 citations), Hardware and Architecture (17 citations) and Signal Processing (27 citations). Pinghui Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xiaohong Guan, Don Towsley, Fabrício Murai, Bruno Ribeiro, Tao Qin, Jing Tao, Junzhou Zhao, John C. S. Lui, Jiefeng Cheng and Zhenguo Li. Their work appears in journals such as ACM Transactions on Information Systems, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Parallel and Distributed Systems and Systems 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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