Shaolong Kuang

986 citations
65 papers · 711 indexed · h-index 12
Topics
Soft Robotics and Applications (16 papers)EEG and Brain-Computer Interfaces (9 papers)Robot Manipulation and Learning (6 papers)
Journals
Nature CommunicationsSHILAP Revista de lepidopterologíaIEEE Access
Partner nations
ChinaUnited StatesJapan

In The Last Decade

Shaolong Kuang

54 papers receiving 703 citations

Peers

Shaolong Kuang
Comparison fields: 5 of 86
  • Biomedical Engineering 305
  • Cognitive Neuroscience 258
  • Electrical and Electronic Engineering 163
  • Cellular and Molecular Neuroscience 127
  • Mechanical Engineering 120
Replace Hongbo Yang with:
Hongbo Yang China
Ali Alazmani United Kingdom
Luca Ascari Italy
Zhidong Wang Japan
Seong Kwang Hong South Korea
Hongjie Hu China
David C. Yates United Kingdom
Dana D. Damian United Kingdom
Siyang Zuo China
Hangue Park United States
Shaolong Kuang relative to Hongbo Yang China Hongbo Yang's profile →
Citations per field
00.5×3.3×
Hongbo Yang · 1×
Citations per year

Countries citing papers authored by Shaolong Kuang

Since Specialization
Citations

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

Fields of papers citing papers by Shaolong Kuang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaolong Kuang

This figure shows the co-authorship network connecting the top 25 collaborators of Shaolong Kuang. A scholar is included among the top collaborators of Shaolong Kuang 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 Shaolong Kuang. Shaolong Kuang 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
#WorkIndexed citations
1 0
2 0
3 1
4 0
5 0
6 0
7 4
8 5
9 2
10 2
11 13
12 18
13 4
14 2
15 24
16 217
17 1
18 2
19 15
20 10

About Shaolong Kuang

Shaolong Kuang is a scholar working on Biomedical Engineering, Health Informatics and Medical Laboratory Technology, having authored 65 papers that have together received 711 indexed citations. Recurring topics across this work include Soft Robotics and Applications (16 papers), EEG and Brain-Computer Interfaces (9 papers) and Robot Manipulation and Learning (6 papers). The work is most often cited by research in Cognitive Neuroscience (258 citations), Human-Computer Interaction (70 citations) and Condensed Matter Physics (96 citations). Shaolong Kuang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Lining Sun, Hongmiao Zhang, Guilin Zhu, Xiangpeng Li, Fangxia Li, Shiwu Zhang, Shi‐Yang Tang, Weihua Li, Jian Shu and Junchen Wang. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Access.

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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