Le Wang

765 citations
53 papers · 412 · h-index 12

Impact in

    • Adversarial Robustness in Machine Learning
    • Anomaly Detection Techniques and Applications
    • Internet Traffic Analysis and Secure E-voting
    • Privacy-Preserving Technologies in Data
    • Topic Modeling
    • Advanced Malware Detection Techniques

Papers in

Le Wang

48 papers receiving 404 citations

Peers

Le Wang
Comparison fields: 5 of 91
  • Artificial Intelligence 223
  • Signal Processing 63
  • Computer Networks and Communications 119
  • Health Informatics 4
  • Information Systems 62
Replace Shanqing Yu with:
Shanqing Yu China
Panagiotis Karampelas Greece
Alexander Shelupanov Russia
Minhao Cheng United States
Huaxin Li China
Emmanouil Magkos Greece
Tianqing Zhu China
Şerif Bahtıyar Türkiye
Sung-Jin Kim South Korea
Le Wang relative to Shanqing Yu China Shanqing Yu's profile →
Citations per field
00.5×1.5×1.8×
Shanqing Yu · 1×
Citations per year

Countries citing papers authored by Le Wang

Since Specialization
Citations

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

Fields of papers citing papers by Le Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202061
2 202335
3 202135
4 202227
5 202325
6 202221
7 200617
8 200417
9 202217
10 200915
11 202013
12 201913
13 202411
14 202210
15 20247
16 20237
17 20226
18 20236
19 20245
20 20065

About Le Wang

Le Wang is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems and Signal Processing, having authored 53 papers that have together received 412 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (15 papers), Anomaly Detection Techniques and Applications (12 papers), Network Security and Intrusion Detection (12 papers), Topic Modeling (6 papers), Advanced Malware Detection Techniques (6 papers), Natural Language Processing Techniques (4 papers), Advanced Neural Network Applications (4 papers) and Quantum Mechanics and Applications (3 papers). The work is most often cited by research in Artificial Intelligence (223 citations), Signal Processing (63 citations), Computer Networks and Communications (119 citations), Health Informatics (4 citations) and Information Systems (62 citations). Le Wang has collaborated with scholars based in China, United States and India. Frequent co-authors include Zhaoquan Gu, Daniel L. Millimet, Zhihong Tian, Muhammad Shafiq, Hui Lu, Lihua Yin, Jukka Manner, Mohsen Guizani, Zhiqiang Zhang and Xiaojiang Du. Their work appears in journals such as IEEE Internet of Things Journal, Applied Sciences, IEEE Transactions on Network Science and Engineering, Computers, materials & continua/Computers, materials & continua (Print) and Computers & Electrical 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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