Liang Pan

4.5k citations
48 papers · 3.8k indexed · 3 hit papers · h-index 29
Topics
Advanced Sensor and Energy Harvesting Materials (20 papers)Advanced Memory and Neural Computing (16 papers)Conducting polymers and applications (14 papers)

In The Last Decade

Liang Pan

43 papers receiving 3.7k citations

Hit Papers

Gesture recognition using a bioinspired learning architec...2018202620202023202020202018100200300400

Peers

Liang Pan
Comparison fields: 5 of 130
  • Biomedical Engineering 1.9k
  • Electrical and Electronic Engineering 1.8k
  • Polymers and Plastics 1.1k
  • Cellular and Molecular Neuroscience 747
  • Cognitive Neuroscience 700
Replace Jie Shang with:
Jie Shang China
Ke He China
Ming Wang China
Lei Wei Singapore
Song Gao China
Dong Jun Lee South Korea
Changyeong Song South Korea
Alessandro Chiolerio Italy
Allister F. McGuire United States
Raphael Pfattner Spain
Liang Pan relative to Jie Shang China Jie Shang's profile →
Citations per field
00.5×1.5×
Jie Shang · 1×
Citations per year

Countries citing papers authored by Liang Pan

Since Specialization
Citations

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

Fields of papers citing papers by Liang Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liang Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Liang Pan. A scholar is included among the top collaborators of Liang Pan 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 Liang Pan. Liang Pan 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 4
3 3
4 0
5 1
6 0
7 0
8 0
9 2
10 43
11 6
12 6
13 65
14 87
15 133
16 159
17
Artificial Skin Perceptionbreakdown →
371
18 68
19 10
20 194

About Liang Pan

Liang Pan is a scholar working on Polymers and Plastics, Biomedical Engineering and Cellular and Molecular Neuroscience, having authored 48 papers that have together received 3.8k indexed citations. Recurring topics across this work include Advanced Sensor and Energy Harvesting Materials (20 papers), Advanced Memory and Neural Computing (16 papers) and Conducting polymers and applications (14 papers). The work is most often cited by research in Polymers and Plastics (1.1k citations), Biomedical Engineering (1.9k citations) and Cellular and Molecular Neuroscience (747 citations). Liang Pan has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Xiaodong Chen, Ming Wang, Changjin Wan, Ke He, Gang Liu, Shaowu Pan, Run‐Wei Li, Jie Shang, Ting Wang and Pingqiang Cai. Their work appears in journals such as Journal of the American Chemical Society, Advanced Materials and Angewandte Chemie International Edition.

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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