Dapeng Wu

4.5k citations
219 papers · 3.4k · h-index 32

Impact in

Papers in

Dapeng Wu

192 papers receiving 3.3k citations

Peers

Dapeng Wu
Comparison fields: 5 of 94
  • Computer Networks and Communications 1.8k
  • Computer Science Applications 222
  • Artificial Intelligence 991
  • Information Systems 650
  • Electrical and Electronic Engineering 1.2k
Replace Nalini Venkatasubramanian with:
Nalini Venkatasubramanian United States
Matthias Hollick Germany
Yanchao Zhang United States
Changqiao Xu China
Guangtao Xue China
He Li China
Abderrahim Benslimane France
Ruchuan Wang China
Liang Zhou China
Dapeng Wu relative to Nalini Venkatasubramanian United States Nalini Venkatasubramanian's profile →
Citations per field
00.5×6.3×
Nalini Venkatasubramanian · 1×
Citations per year

Countries citing papers authored by Dapeng Wu

Since Specialization
Citations

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

Fields of papers citing papers by Dapeng Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 219 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018157
2 2017155
3 2017149
4 2018129
5 2020119
6 2018110
7 201798
8 201597
9 201890
10 201887
11 202380
12 201771
13 201861
14 202060
15 202157
16 202157
17 202155
18 202050
19 201950
20 201849

About Dapeng Wu

Dapeng Wu is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 219 papers that have together received 3.4k indexed citations. Recurring topics across this work include Opportunistic and Delay-Tolerant Networks (44 papers), IoT and Edge/Fog Computing (40 papers), Caching and Content Delivery (36 papers), Cooperative Communication and Network Coding (31 papers), Privacy-Preserving Technologies in Data (30 papers), Mobile Ad Hoc Networks (27 papers), Vehicular Ad Hoc Networks (VANETs) (21 papers) and Software-Defined Networks and 5G (19 papers). The work is most often cited by research in Computer Networks and Communications (1.8k citations), Computer Science Applications (222 citations), Artificial Intelligence (991 citations), Information Systems (650 citations) and Electrical and Electronic Engineering (1.2k citations). Dapeng Wu has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Ruyan Wang, Honggang Wang, Junjie Yan, Zhigang Yang, Puning Zhang, Yaping Cui, Boran Yang, Shaoen Wu, Dalei Wu and Qing Yang. Their work appears in journals such as IEEE Internet of Things Journal, Digital Communications and Networks, IEEE Transactions on Vehicular Technology, IEEE Transactions on Multimedia and IEEE Access.

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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