Pinzhen Chen

464 citations
27 papers · 255 · h-index 8

Impact in

Papers in

    • Natural Language Processing Techniques 15
    • Topic Modeling 11
    • Text Readability and Simplification 3
    • Semantic Web and Ontologies 2
    • Advanced Sensor and Energy Harvesting Materials 6

Pinzhen Chen

21 papers receiving 247 citations

Peers

Pinzhen Chen
Comparison fields: 5 of 55
  • Artificial Intelligence 97
  • Biomedical Engineering 109
  • Polymers and Plastics 31
  • Human-Computer Interaction 8
  • Cognitive Neuroscience 24
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Pinzhen Chen relative to Ziyan Chen China Ziyan Chen's profile →
Citations per field
00.5×2.7×
Ziyan Chen · 1×
Citations per year

Countries citing papers authored by Pinzhen Chen

Since Specialization
Citations

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

Fields of papers citing papers by Pinzhen Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202072
2 202455
3 202336
4 202417
5 202416
6 20209
7 20238
8 20238
9 20237
10 20257
11 20244
12 20243
13 20242
14 20222
15 20232
16 20202
17 20241
18 20231
19 20221
20 20231

About Pinzhen Chen

Pinzhen Chen is a scholar working on Artificial Intelligence, Biomedical Engineering, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 27 papers that have together received 255 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (15 papers), Topic Modeling (11 papers), Advanced Sensor and Energy Harvesting Materials (6 papers), Text Readability and Simplification (3 papers), Conducting polymers and applications (2 papers), Semantic Web and Ontologies (2 papers), Advanced Memory and Neural Computing (2 papers) and Tactile and Sensory Interactions (2 papers). The work is most often cited by research in Artificial Intelligence (97 citations), Biomedical Engineering (109 citations), Polymers and Plastics (31 citations), Human-Computer Interaction (8 citations) and Cognitive Neuroscience (24 citations). Pinzhen Chen has collaborated with scholars based in United Kingdom, China and Bangladesh. Frequent co-authors include Qiongfeng Shi, Shengshun Duan, Jun Wu, Kenneth Heafield, Shengxin Xiang, Jianlong Hong, Guozhen Shen, Barry Haddow, Amir Kamran and William Waites. Their work appears in journals such as Science Advances, Advanced Science, European Radiology, Advanced Materials and Frontiers in Endocrinology.

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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