Jiefei Ding

633 citations
13 papers · 465 indexed · h-index 8

Impact in

Papers in

Jiefei Ding

13 papers receiving 452 citations

Peers

Jiefei Ding
Comparison fields: 5 of 40
  • Computer Networks and Communications 249
  • Automotive Engineering 90
  • Electrical and Electronic Engineering 350
  • Information Systems 94
  • Computer Science Applications 13
Replace Jingyun Feng with:
Jingyun Feng Japan
Stefan Dietzel Germany
Hamid Reza Arkian Iran
Yajuan Qin China
Iftikhar Rasheed Pakistan
Mohamed Nidhal Mejri France
Jason J. Haas United States
Xiaosha Chen China
Muhammad Rizwan Anwar China
Ping Lang China
Jiefei Ding relative to Jingyun Feng Japan Jingyun Feng's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jiefei Ding

Since Specialization
Citations

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

Fields of papers citing papers by Jiefei Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2016109
2 201592
3 201490
4 201549
5 201840
6 201938
7 201525
8 201710
9 20253
10 20153
11 20153
12 20132
13 20241

About Jiefei Ding

Jiefei Ding is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Automotive Engineering, Information Systems and Materials Chemistry, having authored 13 papers that have together received 465 indexed citations. Recurring topics across this work include Advanced Wireless Communication Technologies (4 papers), Advanced MIMO Systems Optimization (4 papers), Caching and Content Delivery (3 papers), Electric Vehicles and Infrastructure (3 papers), Vehicular Ad Hoc Networks (VANETs) (2 papers), Cooperative Communication and Network Coding (2 papers), Cloud Computing and Resource Management (2 papers) and Shape Memory Alloy Transformations (2 papers). The work is most often cited by research in Computer Networks and Communications (249 citations), Automotive Engineering (90 citations), Electrical and Electronic Engineering (350 citations), Information Systems (94 citations) and Computer Science Applications (13 citations). Jiefei Ding has collaborated with scholars based in China, Norway and Canada. Frequent co-authors include Rong Yu, Stein Gjessing, Yan Zhang, Jun Cai, Xumin Huang, Sabita Maharjan, Rong Yu, Yi Liu, Ming‐Tuo Zhou and Weifeng Zhong. Their work appears in journals such as IEEE Transactions on Vehicular Technology, IEEE Internet of Things Journal, IEEE Transactions on Industrial Electronics, IEEE Communications Magazine and IEEE Transactions on Wireless 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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