Bing Song

1.1k total citations
55 papers, 741 citations indexed

About

Bing Song is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Materials Chemistry. According to data from OpenAlex, Bing Song has authored 55 papers receiving a total of 741 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Electrical and Electronic Engineering, 13 papers in Biomedical Engineering and 12 papers in Materials Chemistry. Recurrent topics in Bing Song's work include Advanced Memory and Neural Computing (24 papers), Ferroelectric and Negative Capacitance Devices (12 papers) and Microfluidic and Capillary Electrophoresis Applications (7 papers). Bing Song is often cited by papers focused on Advanced Memory and Neural Computing (24 papers), Ferroelectric and Negative Capacitance Devices (12 papers) and Microfluidic and Capillary Electrophoresis Applications (7 papers). Bing Song collaborates with scholars based in China, United States and Macao. Bing Song's co-authors include Qingjiang Li, Haijun Liu, Sen Liu, Qi Liu, Hui Xu, Yi Sun, Rongrong Cao, Hui Xu, A. K. Sen and Yifan Dai and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Advanced Functional Materials.

In The Last Decade

Bing Song

54 papers receiving 723 citations

Peers

Bing Song
Comparison fields: 5 of 108
  • Electrical and Electronic Engineering 466
  • Materials Chemistry 203
  • Biomedical Engineering 139
  • Cellular and Molecular Neuroscience 123
  • Molecular Biology 77
Replace Beiju Huang with:
Beiju Huang China
Min‐Kyu Song South Korea
Bruno Mercier France
Tommaso Del Rosso Brazil
Cong Zhang China
Daniel Puiu Poenar Singapore
Shiheng Lu China
Yuchen Wang China
Ruofan Li China
Beiju Huang China View profile →
Citations per field, relative to Bing Song
Bing Song · 1×
Citations per year, relative to Bing Song
Bing Song · 1×

Countries citing papers authored by Bing Song

Since Specialization
Citations

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

Fields of papers citing papers by Bing Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bing Song

This figure shows the co-authorship network connecting the top 25 collaborators of Bing Song. A scholar is included among the top collaborators of Bing Song 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 Bing Song. Bing Song 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 2
3 9
4 6
5 2
6 8
7 1
8 0
9 7
10 2
11 117
12 9
13 46
14 62
15 21
16 60
17 4
18 22
19
Data analysis method for glucose detection based on surface plasmon resonance
1
20 9

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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