Changda Wang

701 citations
56 papers · 479 · h-index 14

Impact in

Papers in

Changda Wang

50 papers receiving 465 citations

Peers

Changda Wang
Comparison fields: 5 of 60
  • Computer Networks and Communications 262
  • Information Systems and Management 62
  • Artificial Intelligence 183
  • Signal Processing 57
  • Computer Vision and Pattern Recognition 98
Replace Xiao Fu with:
Xiao Fu China
Benjamín Tovar United States
Emil Vassev Ireland
Hai Jiang United States
Ankur Jain United States
Elaine R. Faria Brazil
Carlos García Garino Argentina
Dongsheng Yang China
Alexander Clemm United States
Kai Zhou United States
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Citations per field
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Citations per year

Countries citing papers authored by Changda Wang

Since Specialization
Citations

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

Fields of papers citing papers by Changda Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201849
2 202140
3 201837
4 201536
5 202124
6 201424
7 201723
8 202118
9 201617
10 202015
11 202214
12 202313
13 201713
14 202213
15 201910
16 201810
17 202110
18 20189
19 20228
20 20237

About Changda Wang

Changda Wang is a scholar working on Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing and Information Systems, having authored 56 papers that have together received 479 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (16 papers), Internet Traffic Analysis and Secure E-voting (12 papers), Chaos-based Image/Signal Encryption (10 papers), Advanced Malware Detection Techniques (9 papers), Scientific Computing and Data Management (9 papers), Cryptographic Implementations and Security (7 papers), Anomaly Detection Techniques and Applications (6 papers) and Coding theory and cryptography (5 papers). The work is most often cited by research in Computer Networks and Communications (262 citations), Information Systems and Management (62 citations), Artificial Intelligence (183 citations), Signal Processing (57 citations) and Computer Vision and Pattern Recognition (98 citations). Changda Wang has collaborated with scholars based in China, United States and Pakistan. Frequent co-authors include Elisa Bertino, Xing Zhang, Syed Rafiul Hussain, Seung-Hyun Seo, Rizwan Akhtar, Yongbao Wu, Wenxue Li, Shiguang Ju, Muhammad Shiraz and Muhammad Khurram Khan. Their work appears in journals such as Wireless Communications and Mobile Computing, Electronics, IEEE Transactions on Information Forensics and Security, IEEE Access and IEEE Transactions on Network Science and 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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