Guanglong Ding

3.8k total citations · 1 hit paper
86 papers, 3.1k citations indexed

About

Guanglong Ding is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Biomedical Engineering. According to data from OpenAlex, Guanglong Ding has authored 86 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Electrical and Electronic Engineering, 26 papers in Materials Chemistry and 22 papers in Biomedical Engineering. Recurrent topics in Guanglong Ding's work include Advanced Memory and Neural Computing (51 papers), Photoreceptor and optogenetics research (13 papers) and Conducting polymers and applications (13 papers). Guanglong Ding is often cited by papers focused on Advanced Memory and Neural Computing (51 papers), Photoreceptor and optogenetics research (13 papers) and Conducting polymers and applications (13 papers). Guanglong Ding collaborates with scholars based in China, Hong Kong and Taiwan. Guanglong Ding's co-authors include Su‐Ting Han, Ye Zhou, Kui Zhou, Yongsong Cao, Mingcheng Guo, Chen Zhang, Wenbing Zhang, Jia‐Qin Yang, Ruosi Chen and Gang Tang and has published in prestigious journals such as Chemical Reviews, Chemical Society Reviews and Advanced Materials.

In The Last Decade

Guanglong Ding

82 papers receiving 3.1k citations

Hit Papers

Bioinspired Artificial Sensory Nerve Based on Nafion Memr... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers

Guanglong Ding
Comparison fields: 5 of 100
  • Electrical and Electronic Engineering 1.8k
  • Materials Chemistry 895
  • Biomedical Engineering 832
  • Cellular and Molecular Neuroscience 579
  • Polymers and Plastics 555
Replace Li Guo with:
Li Guo China
Long Chen China
Hongji Li China
Mihai Irimia‐Vladu Austria
Dandan Hao China
Zheng Fang China
Bin Zhang China
Guodong Wei China
Tania Roy United States
Marcos Pita Spain
Li Guo China View profile →
Citations per field, relative to Guanglong Ding
Guanglong Ding · 1×
Citations per year, relative to Guanglong Ding
Guanglong Ding · 1×

Countries citing papers authored by Guanglong Ding

Since Specialization
Citations

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

Fields of papers citing papers by Guanglong Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guanglong Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Guanglong Ding. A scholar is included among the top collaborators of Guanglong Ding 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 Guanglong Ding. Guanglong Ding 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 4
4 9
5 6
6 8
7 2
8 9
9 24
10 4
11 11
12 22
13 52
14 36
15 40
16 39
17 13
18 50
19 57
20
Bioinspired Artificial Sensory Nerve Based on Nafion Memristor breakdown →
284

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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