Jiadai Wang

2.4k citations
51 papers · 1.7k indexed · 2 hit papers · h-index 17
Topics
Software-Defined Networks and 5G (21 papers)Vehicular Ad Hoc Networks (VANETs) (10 papers)IoT and Edge/Fog Computing (9 papers)
Partner nations
ChinaJapanCanada

In The Last Decade

Jiadai Wang

43 papers receiving 1.7k citations

Hit Papers

Networking and Communications in Autonomous Driving: A Su...201820262020202320182019100200300400

Peers

Jiadai Wang
Comparison fields: 5 of 95
  • Computer Networks and Communications 961
  • Electrical and Electronic Engineering 784
  • Artificial Intelligence 308
  • Information Systems 305
  • Aerospace Engineering 211
Replace Gunasekaran Raja with:
Gunasekaran Raja India
Ghulam Abbas Pakistan
Mushu Li Canada
Soumaya Cherkaoui Canada
Kai Lin China
Saba Al–Rubaye United Kingdom
Junhui Zhao China
Chaker Abdelaziz Kerrache Algeria
Jianqi Liu China
Jiadai Wang relative to Gunasekaran Raja India Gunasekaran Raja's profile →
Citations per field
00.5×1.5×2.3×
Gunasekaran Raja · 1×
Citations per year

Countries citing papers authored by Jiadai Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jiadai Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiadai Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Jiadai Wang. A scholar is included among the top collaborators of Jiadai Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jiadai Wang. Jiadai Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 6
2 1
3 1
4 14
5 0
6 0
7 0
8 0
9 27
10 11
11 10
12 53
13 0
14 1
15 81
16 15
17 144
18
Smart Resource Allocation for Mobile Edge Computing: A Deep Reinforcement Learning Approachbreakdown →
346
19 49
20
Networking and Communications in Autonomous Driving: A Surveybreakdown →
402

About Jiadai Wang

Jiadai Wang is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Signal Processing, having authored 51 papers that have together received 1.7k indexed citations. Recurring topics across this work include Software-Defined Networks and 5G (21 papers), Vehicular Ad Hoc Networks (VANETs) (10 papers) and IoT and Edge/Fog Computing (9 papers). The work is most often cited by research in Computer Networks and Communications (961 citations), Electrical and Electronic Engineering (784 citations) and Information Systems (305 citations). Jiadai Wang has collaborated with scholars based in China, Japan and Canada. Frequent co-authors include Jiajia Liu, Nei Kato, Lei Zhao, Yawen Tan, Yurui Cao, Yuanyuan Sun, Hongzhi Guo, Jingyi Li, Yijie Xun and Yanning Zhang. Their work appears in journals such as IEEE Communications Surveys & Tutorials, International Journal of Hydrogen Energy and IEEE Journal on Selected Areas in Communications.

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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