Song Fu

3.6k total citations
164 papers, 2.4k citations indexed

About

Song Fu is a scholar working on Computer Networks and Communications, Information Systems and Artificial Intelligence. According to data from OpenAlex, Song Fu has authored 164 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Computer Networks and Communications, 39 papers in Information Systems and 33 papers in Artificial Intelligence. Recurrent topics in Song Fu's work include Cloud Computing and Resource Management (33 papers), Software System Performance and Reliability (26 papers) and Distributed and Parallel Computing Systems (21 papers). Song Fu is often cited by papers focused on Cloud Computing and Resource Management (33 papers), Software System Performance and Reliability (26 papers) and Distributed and Parallel Computing Systems (21 papers). Song Fu collaborates with scholars based in United States, China and United Kingdom. Song Fu's co-authors include Chengzhong Xu, Sihai Tang, Qing Yang, Qiang Guan, Ziming Zhang, Qing Yang, Qi Chen, Jingda Guo, Qi Chen and Xu Ma and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Internet of Things Journal.

In The Last Decade

Song Fu

147 papers receiving 2.3k citations

Peers

Song Fu
Comparison fields: 5 of 97
  • Computer Networks and Communications 1.3k
  • Information Systems 678
  • Artificial Intelligence 584
  • Computer Vision and Pattern Recognition 536
  • Electrical and Electronic Engineering 461
Replace Yiu-Wing Leung with:
Yiu-Wing Leung Hong Kong
Hongbin Sun China
Nils Ole Tippenhauer Singapore
Dafang Zhang China
Shaoshan Liu United States
Li Erran Li United States
Thambipillai Srikanthan Singapore
Yuan Zhou China
Qi Qi China
Shinpei Kato Japan
Yiu-Wing Leung Hong Kong View profile →
Citations per field, relative to Song Fu
Song Fu · 1×
Citations per year, relative to Song Fu
Song Fu · 1×

Countries citing papers authored by Song Fu

Since Specialization
Citations

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

Fields of papers citing papers by Song Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Song Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Song Fu. A scholar is included among the top collaborators of Song Fu 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 Fu. Song Fu 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 1
2 1
3 0
4 0
5 4
6 0
7 0
8 2
9 0
10 3
11 1
12 5
13 32
14 99
15 61
16 1
17
ASSESSING GAUGE RELIABILITY AND REPRODUCIBILITY USING THE CORRELATION BETWEEN TWO MEASUREMENT SYSTEMS
1
18 17
19 28
20 7

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026