Jinmei Shu
- Computer Networks and Communications top 5%
- Electrical and Electronic Engineering
- Artificial Intelligence
- Computer Vision and Pattern Recognition top 10%
- Automotive Engineering top 10%
- Co-authors
- Geyong MinHongbo JiangZhu XiaoZhu HanHongyang ChenJiangchuan LiuJohn C. S. LuiSchahram Dustdar
- Topics
- IoT and Edge/Fog Computing (2 papers)Autonomous Vehicle Technology and Safety (2 papers)Advanced Neural Network Applications (2 papers)
- Cited by
- Computer Networks and CommunicationsAutomotive EngineeringComputer Vision and Pattern Recognition
- Journals
- IEEE Journal on Selected Areas in CommunicationsIEEE Transactions on Mobile ComputingIEEE Network
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Jinmei Shu
5 papers receiving 362 citations
Hit Papers
Peers
Comparison fields: 5 of 53
- Computer Networks and Communications 190
- Electrical and Electronic Engineering 120
- Artificial Intelligence 78
- Computer Vision and Pattern Recognition 73
- Automotive Engineering 68
Countries citing papers authored by Jinmei Shu
This map shows the geographic impact of Jinmei Shu'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 Jinmei Shu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinmei Shu more than expected).
Fields of papers citing papers by Jinmei Shu
This network shows the impact of papers produced by Jinmei Shu. 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 Jinmei Shu. The network helps show where Jinmei Shu may publish in the future.
Co-authorship network of co-authors of Jinmei Shu
This figure shows the co-authorship network connecting the top 25 collaborators of Jinmei Shu. A scholar is included among the top collaborators of Jinmei Shu 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 Jinmei Shu. Jinmei Shu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 48 | |
| 2 | 1 | |
| 3 | 59 | |
| 4 | Multi-Objective Parallel Task Offloading and Content Caching in D2D-aided MEC Networksbreakdown → | 126 |
| 5 | 136 |
About Jinmei Shu
Jinmei Shu is a scholar working on Automotive Engineering, Complementary and alternative medicine and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 370 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (2 papers), Autonomous Vehicle Technology and Safety (2 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Computer Networks and Communications (190 citations), Automotive Engineering (68 citations) and Computer Vision and Pattern Recognition (73 citations). Jinmei Shu has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Geyong Min, Hongbo Jiang, Zhu Xiao, Zhu Han, Hongyang Chen, Jiangchuan Liu, John C. S. Lui, Schahram Dustdar, Arun Iyengar and Jinwen Liang. Their work appears in journals such as IEEE Journal on Selected Areas in Communications, IEEE Transactions on Mobile Computing and IEEE Network.
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.