Wei Wan

934 citations
63 papers · 697 · h-index 11

Impact in

    • Sentiment Analysis and Opinion Mining
    • Advanced Text Analysis Techniques
    • Topic Modeling
    • Privacy-Preserving Technologies in Data
    • Text and Document Classification Technologies
    • Adversarial Robustness in Machine Learning
    • Spam and Phishing Detection

Papers in

Wei Wan

53 papers receiving 657 citations

Peers

Wei Wan
Comparison fields: 5 of 86
  • Artificial Intelligence 487
  • Information Systems 110
  • Information Systems and Management 25
  • Statistical and Nonlinear Physics 42
  • Computer Networks and Communications 62
Replace A. O. Bolivar with:
A. O. Bolivar Brazil
Liang Hu China
Daniele Regoli Italy
K. Ch. Chatzisavvas Greece
Kristina Lisa Klinkner United States
Xiaoyu Liu China
Alexander Panchenko Russia
Wei Wan relative to A. O. Bolivar Brazil A. O. Bolivar's profile →
Citations per field
00.5×10×20×30×
A. O. Bolivar · 1×
Citations per year

Countries citing papers authored by Wei Wan

Since Specialization
Citations

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

Fields of papers citing papers by Wei Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012203
2 2016106
3 201260
4 202256
5 201630
6 202225
7 201021
8 202120
9 202411
10 201410
11 201310
12 20248
13 20168
14 20168
15 20188
16 20088
17 20097
18 20247
19 20136
20 20245

About Wei Wan

Wei Wan is a scholar working on Artificial Intelligence, Computer Networks and Communications, Atomic and Molecular Physics, and Optics, Molecular Biology and Computer Vision and Pattern Recognition, having authored 63 papers that have together received 697 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (10 papers), Quantum Information and Cryptography (9 papers), Network Security and Intrusion Detection (9 papers), Privacy-Preserving Technologies in Data (7 papers), Cold Atom Physics and Bose-Einstein Condensates (7 papers), Quantum Mechanics and Applications (4 papers), Internet Traffic Analysis and Secure E-voting (4 papers) and Quantum optics and atomic interactions (4 papers). The work is most often cited by research in Artificial Intelligence (487 citations), Information Systems (110 citations), Information Systems and Management (25 citations), Statistical and Nonlinear Physics (42 citations) and Computer Networks and Communications (62 citations). Wei Wan has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Hua Xu, Wenhao Zhang, Shengshan Hu, Leo Yu Zhang, Tengjiao Wang, Xiao Zhang, Wei Chen, Wei Wang, Junyu Shi and Mang Feng. Their work appears in journals such as Chinese Physics Letters, Scientific Reports, Expert Systems with Applications, IEEE Transactions on Information Forensics and Security and Physical Review A.

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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