Supin Chen

1.1k citations
25 papers · 810 · h-index 13

Impact in

Papers in

Supin Chen

24 papers receiving 802 citations

Peers

Supin Chen
Comparison fields: 5 of 62
  • Cellular and Molecular Neuroscience 278
  • Cognitive Neuroscience 190
  • Biomedical Engineering 407
  • Pharmaceutical Science 43
  • Electrical and Electronic Engineering 366
Replace Antonio Balena with:
Antonio Balena Italy
Jingshan Mo China
Don‐Wook Lee South Korea
Jong‐ryul Choi South Korea
Hiroaki Takehara Japan
F.J. Blanco Spain
Elisabetta Colombo Italy
Filippo Pisano Italy
Kee Scholten United States
Anton Bukatin Russia
Supin Chen relative to Antonio Balena Italy Antonio Balena's profile →
Citations per field
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Citations per year

Countries citing papers authored by Supin Chen

Since Specialization
Citations

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

Fields of papers citing papers by Supin Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018233
2 2011153
3 201250
4 201248
5 201946
6 201340
7 201338
8 200638
9 201336
10 201333
11 201824
12 201322
13 201915
14 201910
15 20207
16 20145
17 20192
18 20142
19 20192
20
OPTIMIZATION OF RADIOSYNTHESIS OF MOLECULAR TRACERS IN EWOD MICROFLUIDIC CHIP
20102

About Supin Chen

Supin Chen is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Cellular and Molecular Neuroscience, Mechanical Engineering and Cognitive Neuroscience, having authored 25 papers that have together received 810 indexed citations. Recurring topics across this work include Electrowetting and Microfluidic Technologies (16 papers), Microfluidic and Capillary Electrophoresis Applications (10 papers), Innovative Microfluidic and Catalytic Techniques Innovation (7 papers), Biosensors and Analytical Detection (6 papers), Neuroscience and Neural Engineering (5 papers), Modular Robots and Swarm Intelligence (5 papers), Neural dynamics and brain function (3 papers) and Environmental Monitoring and Data Management (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (278 citations), Cognitive Neuroscience (190 citations), Biomedical Engineering (407 citations), Pharmaceutical Science (43 citations) and Electrical and Electronic Engineering (366 citations). Supin Chen has collaborated with scholars based in United States, Russia and South Korea. Frequent co-authors include Chang‐Jin Kim, R. Michael van Dam, Pei Yuin Keng, Gaurav J. Shah, Huijiang Ding, Saman Sadeghi, Angela Tooker, Vanessa Tolosa, Alex A. Dooraghi and Arion F. Chatziioannou. Their work appears in journals such as Lab on a Chip, Journal of Visualized Experiments, Journal of Nuclear Medicine, Journal of Micromechanics and Microengineering and Applied Physics Letters.

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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