Song Yang

2.3k total citations
126 papers, 1.5k citations indexed

About

Song Yang is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Song Yang has authored 126 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computer Networks and Communications, 36 papers in Electrical and Electronic Engineering and 21 papers in Computer Vision and Pattern Recognition. Recurrent topics in Song Yang's work include Software-Defined Networks and 5G (20 papers), Advanced Optical Network Technologies (16 papers) and IoT and Edge/Fog Computing (14 papers). Song Yang is often cited by papers focused on Software-Defined Networks and 5G (20 papers), Advanced Optical Network Technologies (16 papers) and IoT and Edge/Fog Computing (14 papers). Song Yang collaborates with scholars based in China, United States and Netherlands. Song Yang's co-authors include Fan Li, Xiaoming Fu, Yu Wang, Stojan Trajanovski, Fernando Kuipers, Ramin Yahyapour, Xu Chen, Yue Wu, Fan Li and Yadong Xie and has published in prestigious journals such as Remote Sensing of Environment, Physical Review A and Materials Science and Engineering A.

In The Last Decade

Song Yang

111 papers receiving 1.5k citations

Peers

Song Yang
Comparison fields: 5 of 104
  • Computer Networks and Communications 697
  • Electrical and Electronic Engineering 426
  • Information Systems 262
  • Artificial Intelligence 203
  • Computer Vision and Pattern Recognition 170
Replace Thomas Newe with:
Thomas Newe Ireland
Dalei Wu United States
Yi‐Chao Chen China
Jiacheng Wang China
Shaiful Jahari Hashim Malaysia
Yanjing Sun China
Min Zhao China
Sang‐Woo Lee South Korea
Chenhan Xu United States
Thomas Newe Ireland View profile →
Citations per field, relative to Song Yang
Song Yang · 1×
Citations per year, relative to Song Yang
Song Yang · 1×

Countries citing papers authored by Song Yang

Since Specialization
Citations

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

Fields of papers citing papers by Song Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Song Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Song Yang. A scholar is included among the top collaborators of Song Yang 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 Song Yang. Song Yang 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
# Work Indexed citations
1 2
2 0
3 0
4 0
5 2
6 0
7 1
8 1
9 5
10 0
11 0
12 4
13 4
14 13
15 15
16 45
17 55
18 23
19 17
20
Cascade force control of lower limb hydraulic exoskeleton for human performance augmentation
1

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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