Yusheng Ji

11.2k citations
455 papers · 8.1k indexed · 2 hit papers · h-index 42

Yusheng Ji

424 papers receiving 7.9k citations

Hit Papers

Federated Learning for Vehicular Internet of Things: Rece...2622018202620202023100200300400500

Peers

Yusheng Ji
Comparison fields: 5 of 123
  • Computer Networks and Communications 5.3k
  • Electrical and Electronic Engineering 4.5k
  • Computer Vision and Pattern Recognition 1.2k
  • Information Systems 1.2k
  • Signal Processing 562
Replace Tie Qiu with:
Tie Qiu China
Tom H. Luan China
Linghe Kong China
Qiang Ni United Kingdom
Jonathan Rodrı́guez Portugal
Zhaolong Ning China
Rajesh K. Gupta United States
Moayad Aloqaily United Arab Emirates
Zhi Liu China
Tarik Taleb Finland
Yusheng Ji relative to Tie Qiu China Tie Qiu's profile →
Citations per field
00.5×3.5×
Tie Qiu · 1×
Citations per year

Countries citing papers authored by Yusheng Ji

Since Specialization
Citations

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

Fields of papers citing papers by Yusheng Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20250
4 202416
5 202312
6 20232
7 202310
8 202315
9 20220
10 20219
11 20214
12 202137
13 20206
14
Deep Convolutional LSTM Network-based Traffic Matrix Prediction with Partial Information
201926
15 201816
16 20184
17
HVC: A Hybrid Cloud Computing Framework in Vehicular Environment
20172
18
Leveraging RF-channel fluctuation for activity recognition: Active and passive systems, continuous and RSSI-based signal features
201317
19 200710
20 20065

About Yusheng Ji

Yusheng Ji is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Signal Processing, having authored 455 papers that have together received 8.1k indexed citations. Recurring topics across this work include Cooperative Communication and Network Coding (91 papers), Mobile Ad Hoc Networks (87 papers), Advanced MIMO Systems Optimization (78 papers), Vehicular Ad Hoc Networks (VANETs) (72 papers), Opportunistic and Delay-Tolerant Networks (64 papers), Advanced Wireless Network Optimization (57 papers), IoT and Edge/Fog Computing (48 papers) and Energy Efficient Wireless Sensor Networks (46 papers). The work is most often cited by research in Computer Networks and Communications (5.3k citations), Electrical and Electronic Engineering (4.5k citations) and Computer Vision and Pattern Recognition (1.2k citations). Yusheng Ji has collaborated with scholars based in Japan, China and Finland. Frequent co-authors include Celimuge Wu, Zhi Liu, Tsutomu Yoshinaga, Jie Li, Stephan Sigg, Mehdi Bennis, Honggang Zhang, Yu Gu, Shuyu Shi and Xianfu Chen. Their work appears in journals such as IEEE Transactions on Vehicular Technology, IEEE Access, IEEE Internet of Things Journal, Sensors 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.

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