Fengwei Wang

2.1k citations
91 papers · 1.4k · h-index 21

Impact in

Papers in

    • Privacy-Preserving Technologies in Data 43
    • Cryptography and Data Security 39
    • Stochastic Gradient Optimization Techniques 9
    • Adversarial Robustness in Machine Learning 5

Fengwei Wang

80 papers receiving 1.4k citations

Peers

Fengwei Wang
Comparison fields: 5 of 133
  • Artificial Intelligence 573
  • Health Informatics 21
  • Computer Science Applications 54
  • Computational Mathematics 5
  • Cancer Research 103
Replace Shengbo Chen with:
Shengbo Chen China
Waibhav Tembe United States
Lan Huang China
Jun Sakuma Japan
Lingjiao Chen China
Hao Yang China
Daniel Glez‐Peña Spain
Jamie P. McCusker United States
Yu‐Yen Ou Taiwan
Ioannis Kavakiotis Greece
Fengwei Wang relative to Shengbo Chen China Shengbo Chen's profile →
Citations per field
00.5×2.6×
Shengbo Chen · 1×
Citations per year

Countries citing papers authored by Fengwei Wang

Since Specialization
Citations

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

Fields of papers citing papers by Fengwei Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019193
2 2014119
3 2020116
4 202271
5 202062
6 201857
7 200152
8 202249
9 201636
10 200534
11 202233
12 201932
13 202329
14 202228
15 201827
16 202227
17 202125
18 202124
19 201523
20 201722

About Fengwei Wang

Fengwei Wang is a scholar working on Artificial Intelligence, Molecular Biology, Information Systems, Computer Networks and Communications and Computational Theory and Mathematics, having authored 91 papers that have together received 1.4k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (43 papers), Cryptography and Data Security (39 papers), Stochastic Gradient Optimization Techniques (9 papers), Complexity and Algorithms in Graphs (7 papers), Adversarial Robustness in Machine Learning (5 papers), Mobile Crowdsensing and Crowdsourcing (4 papers), Cloud Data Security Solutions (4 papers) and Advanced Steganography and Watermarking Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (573 citations), Health Informatics (21 citations), Computer Science Applications (54 citations), Computational Mathematics (5 citations) and Cancer Research (103 citations). Fengwei Wang has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Hui Zhu, Rongxing Lu, Hui Li, Yandong Zheng, Tuo Hu, Zhenxing Liang, Chi Zhou, Xiaobin Zheng, Xianrui Wu and Ping Lan. Their work appears in journals such as IEEE Transactions on Information Forensics and Security, Information Sciences, IEEE Internet of Things Journal, IEEE Transactions on Dependable and Secure Computing and IEEE Transactions on Services Computing.

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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