Jing Song

618 citations
23 papers · 472 · h-index 9

Impact in

    • Biosensors and Analytical Detection
    • Innovative Microfluidic and Catalytic Techniques Innovation
    • Microfluidic and Capillary Electrophoresis Applications
    • Vehicle Dynamics and Control Systems

Papers in

Jing Song

19 papers receiving 465 citations

Peers

Jing Song
Comparison fields: 5 of 87
  • Biomedical Engineering 321
  • Automotive Engineering 60
  • Bioengineering 21
  • Biophysics 19
  • Infectious Diseases 47
Replace Seungwan Kim with:
Seungwan Kim South Korea
Alexander Lambert United States
Rongrong Sun China
Germán Cómina Peru
Manish Bhaiyya India
Chan-Chiung Liu Taiwan
Pin‐Chuan Chen Taiwan
Ilona Piekarz Poland
Abdelaziz Yousif Ahmed Malaysia
Shivam Singh India
Jing Song relative to Seungwan Kim South Korea Seungwan Kim's profile →
Citations per field
00.5×3.9×
Seungwan Kim · 1×
Citations per year

Countries citing papers authored by Jing Song

Since Specialization
Citations

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

Fields of papers citing papers by Jing Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018246
2 200948
3 202141
4 202233
5 202121
6 200918
7 202311
8 202211
9 20208
10 20237
11 20237
12 20225
13 20174
14 20253
15 20153
16 20122
17 20222
18 20231
19 20141
20 20250

About Jing Song

Jing Song is a scholar working on Biomedical Engineering, Electrical and Electronic Engineering, Automotive Engineering, Control and Systems Engineering and Mechanical Engineering, having authored 23 papers that have together received 472 indexed citations. Recurring topics across this work include Innovative Microfluidic and Catalytic Techniques Innovation (10 papers), Microfluidic and Capillary Electrophoresis Applications (7 papers), Electrowetting and Microfluidic Technologies (3 papers), Catalytic Processes in Materials Science (3 papers), Reliability and Maintenance Optimization (2 papers), Vehicle Dynamics and Control Systems (2 papers), Advanced Battery Technologies Research (2 papers) and Adaptive Control of Nonlinear Systems (2 papers). The work is most often cited by research in Biomedical Engineering (321 citations), Automotive Engineering (60 citations), Bioengineering (21 citations), Biophysics (19 citations) and Infectious Diseases (47 citations). Jing Song has collaborated with scholars based in China, Uzbekistan and United States. Frequent co-authors include Dandan Xu, Xing Ma, Jin Chen, Ji‐Xuan Liu, Jinhong Guo, Xiwei Huang, Jian Deng, Guangsheng Luo, Chencan Du and Liang Kong. Their work appears in journals such as Chemical Engineering Science, Reaction Chemistry & Engineering, Measurement, Scientific Reports and Journal of Flow Chemistry.

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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