Junren Chen

611 citations
28 papers · 465 · h-index 12

Impact in

Papers in

Junren Chen

23 papers receiving 456 citations

Peers

Junren Chen
Comparison fields: 5 of 55
  • Renewable Energy, Sustainability and the Environment 178
  • Computational Mathematics 6
  • Electrical and Electronic Engineering 327
  • Surfaces, Coatings and Films 29
  • Computational Mechanics 48
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Narender Rana United States
Tong Zhou China
Yuhui Huang China
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Citations per field
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Citations per year

Countries citing papers authored by Junren Chen

Since Specialization
Citations

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

Fields of papers citing papers by Junren Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019119
2 201951
3 202043
4 202042
5 202036
6 201028
7 201918
8 201017
9 202217
10 202114
11 202013
12 202312
13 202311
14 202310
15 20238
16 20235
17 20195
18 20234
19 20243
20 20223

About Junren Chen

Junren Chen is a scholar working on Electrical and Electronic Engineering, Computational Mechanics, Computer Vision and Pattern Recognition, Renewable Energy, Sustainability and the Environment and Biomedical Engineering, having authored 28 papers that have together received 465 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (8 papers), Fuel Cells and Related Materials (5 papers), Electrocatalysts for Energy Conversion (5 papers), Optical measurement and interference techniques (4 papers), Advanced Memory and Neural Computing (4 papers), Advanced battery technologies research (4 papers), Ferroelectric and Negative Capacitance Devices (3 papers) and Surface Modification and Superhydrophobicity (3 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (178 citations), Computational Mathematics (6 citations), Electrical and Electronic Engineering (327 citations), Surfaces, Coatings and Films (29 citations) and Computational Mechanics (48 citations). Junren Chen has collaborated with scholars based in China, Hong Kong and Saudi Arabia. Frequent co-authors include Xiaohui Yan, Chen Lin, Michael K. Ng, Zhifeng Zheng, Guanghua Wei, Shuiyun Shen, Jianshi Tang, He Qian, Bin Gao and Huaqiang Wu. Their work appears in journals such as The Journal of Physical Chemistry C, IEEE Transactions on Information Theory, SIAM Journal on Imaging Sciences, IEEE Transactions on Signal Processing and IEEE Transactions on Electron Devices.

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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