Ruichen Li

746 citations
26 papers · 357 · h-index 11

Impact in

Papers in

Ruichen Li

24 papers receiving 353 citations

Peers

Ruichen Li
Comparison fields: 5 of 59
  • Experimental and Cognitive Psychology 104
  • Signal Processing 63
  • Artificial Intelligence 169
  • Computer Vision and Pattern Recognition 70
  • Electronic, Optical and Magnetic Materials 47
Replace Yuanzhi Wang with:
Yuanzhi Wang China
Milan Sečujski Serbia
Lingsheng Kong China
Changliang Li China
C. H. Coker United States
Bikash Chandra Sahana India
Rui Xia China
Ruichen Li relative to Yuanzhi Wang China Yuanzhi Wang's profile →
Citations per field
00.5×3.4×
Yuanzhi Wang · 1×
Citations per year

Countries citing papers authored by Ruichen Li

Since Specialization
Citations

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

Fields of papers citing papers by Ruichen Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021111
2 201831
3 202325
4 202224
5 202322
6 202419
7 201919
8 202318
9 202217
10 202316
11 202310
12 20219
13 20247
14 20237
15 20245
16 20254
17 20243
18 20243
19 20222
20 20241

About Ruichen Li

Ruichen Li is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Aerospace Engineering, having authored 26 papers that have together received 357 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (5 papers), Metamaterials and Metasurfaces Applications (4 papers), Topic Modeling (3 papers), Antenna Design and Analysis (2 papers), Music and Audio Processing (2 papers), Privacy-Preserving Technologies in Data (2 papers), Underwater Acoustics Research (2 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Experimental and Cognitive Psychology (104 citations), Signal Processing (63 citations), Artificial Intelligence (169 citations), Computer Vision and Pattern Recognition (70 citations) and Electronic, Optical and Magnetic Materials (47 citations). Ruichen Li has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Qin Jin, Jinming Zhao, Shizhe Chen, Bin Zheng, Hongsheng Chen, Lian Shen, Xiaofeng Li, Rongrong Zhu, Tong Cai and Haizhou Li. Their work appears in journals such as Laser & Photonics Review, Applied Sciences, Multimedia Tools and Applications, Nanophotonics and Advanced Functional Materials.

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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