Junfeng Li

1.3k citations
142 papers · 839 · h-index 14

Impact in

Papers in

Junfeng Li

125 papers receiving 802 citations

Peers

Junfeng Li
Comparison fields: 5 of 108
  • Signal Processing 406
  • Computational Mechanics 269
  • Cognitive Neuroscience 172
  • Artificial Intelligence 119
  • Speech and Hearing 20
Replace Takanobu Nishiura with:
Takanobu Nishiura Japan
Ning Ma United Kingdom
Manuel Rosa-Zurera Spain
Mahesh Chandra India
Katsutoshi Itoyama Japan
Athanasios Mouchtaris Greece
Mohammed Bahoura Canada
Hong Kook Kim South Korea
Chengshi Zheng China
Martin Bouchard Canada
Junfeng Li relative to Takanobu Nishiura Japan Takanobu Nishiura's profile →
Citations per field
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Takanobu Nishiura · 1×
Citations per year

Countries citing papers authored by Junfeng Li

Since Specialization
Citations

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

Fields of papers citing papers by Junfeng Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 142 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201158
2 201038
3 200533
4 202330
5 201128
6 202325
7 200522
8 202122
9 201421
10 200519
11 201717
12 201615
13 202015
14 202214
15 200813
16 201213
17 200612
18 202212
19 201912
20 202411

About Junfeng Li

Junfeng Li is a scholar working on Signal Processing, Computational Mechanics, Cognitive Neuroscience, Artificial Intelligence and Biomedical Engineering, having authored 142 papers that have together received 839 indexed citations. Recurring topics across this work include Speech and Audio Processing (77 papers), Hearing Loss and Rehabilitation (47 papers), Advanced Adaptive Filtering Techniques (43 papers), Acoustic Wave Phenomena Research (15 papers), Speech Recognition and Synthesis (13 papers), Blind Source Separation Techniques (11 papers), Music and Audio Processing (8 papers) and Advanced SAR Imaging Techniques (7 papers). The work is most often cited by research in Signal Processing (406 citations), Computational Mechanics (269 citations), Cognitive Neuroscience (172 citations), Artificial Intelligence (119 citations) and Speech and Hearing (20 citations). Junfeng Li has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Yonghong Yan, Masato Akagi, Ming‐Jiu Ni, Yôiti Suzuki, Shuichi Sakamoto, Yongtao Yang, Ziteng Wang, Yonghua Cai, Robert Wang and Pingping Lu. Their work appears in journals such as The Journal of the Acoustical Society of America, Applied Acoustics, IEEE Transactions on Geoscience and Remote Sensing, Applied Sciences and Speech Communication.

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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