Song Wang

905 total citations
64 papers, 486 citations indexed

About

Song Wang is a scholar working on Astronomy and Astrophysics, Instrumentation and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Song Wang has authored 64 papers receiving a total of 486 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Astronomy and Astrophysics, 22 papers in Instrumentation and 7 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Song Wang's work include Stellar, planetary, and galactic studies (40 papers), Astronomy and Astrophysical Research (22 papers) and Astrophysics and Star Formation Studies (20 papers). Song Wang is often cited by papers focused on Stellar, planetary, and galactic studies (40 papers), Astronomy and Astrophysical Research (22 papers) and Astrophysics and Star Formation Studies (20 papers). Song Wang collaborates with scholars based in China, United States and Australia. Song Wang's co-authors include Jifeng Liu, Jun Ma, Wen Hu, Yongqian Lei, Feng Cao, Liang Zhou, Weidong Shi, Hongjie Zhang, Shuyan Song and Yu Bai and has published in prestigious journals such as Nature, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Song Wang

51 papers receiving 436 citations

Peers

Song Wang
Comparison fields: 5 of 76
  • Astronomy and Astrophysics 261
  • Instrumentation 116
  • Materials Chemistry 74
  • Electrical and Electronic Engineering 56
  • Biomedical Engineering 56
Replace Masayuki Miyazaki with:
Masayuki Miyazaki Japan
P. Sybilski Poland
Xiang‐Yu Wang China
J. Monin France
N.A. Yusuf Jordan
Marshall J. Styczinski United States
C. Ducourant France
R. P. Verma India
M. Stehle Germany
N. Arend Germany
Masayuki Miyazaki Japan View profile →
Citations per field, relative to Song Wang
Song Wang · 1×
Citations per year, relative to Song Wang
Song Wang · 1×

Countries citing papers authored by Song Wang

Since Specialization
Citations

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

Fields of papers citing papers by Song Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Song Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Song Wang. A scholar is included among the top collaborators of Song Wang 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 Wang. Song Wang 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 0
2 0
3 0
4 8
5 9
6 2
7 1
8 4
9 5
10 4
11 13
12 2
13
Machine Learning Applied to STAR-GALAXY-QSO Classification of The Javalambre-Photometric Local Universe Survey
2
14 3
15 7
16 5
17 21
18 4
19 1
20 99

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