Junfeng Li

1.3k citations
146 papers · 867 · h-index 15

Impact in

Papers in

Junfeng Li

129 papers receiving 828 citations

Peers

Junfeng Li
Comparison fields: 5 of 108
  • Signal Processing 420
  • Computational Mechanics 279
  • Cognitive Neuroscience 178
  • Artificial Intelligence 127
  • Speech and Hearing 20
Replace Takanobu Nishiura with:
Takanobu Nishiura Japan
Ning Ma United Kingdom
Katsutoshi Itoyama Japan
Mahesh Chandra India
Athanasios Mouchtaris Greece
Marco Crocco Italy
Jesper Kjær Nielsen Denmark
Mohammed Bahoura Canada
José J. López Spain
Hong Kook Kim South Korea
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 146 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201158
2 201039
3 200534
4 202330
5 201128
6 202325
7 200523
8 202122
9 200521
10 201421
11 201718
12 202018
13 201216
14 201615
15 202214
16 200813
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 146 papers that have together received 867 indexed citations. Recurring topics across this work include Speech and Audio Processing (79 papers), Hearing Loss and Rehabilitation (48 papers), Advanced Adaptive Filtering Techniques (44 papers), Acoustic Wave Phenomena Research (15 papers), Speech Recognition and Synthesis (13 papers), Blind Source Separation Techniques (11 papers), Music and Audio Processing (9 papers) and Advanced SAR Imaging Techniques (7 papers). The work is most often cited by research in Signal Processing (420 citations), Computational Mechanics (279 citations), Cognitive Neuroscience (178 citations), Artificial Intelligence (127 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, Xiang Ao, Pingping Lu and Guozhong Dai. Their work appears in journals such as The Journal of the Acoustical Society of America, Applied Acoustics, IEEE Transactions on Geoscience and Remote Sensing, IEEE Signal Processing Letters and IEEE/ACM Transactions on Audio Speech and Language Processing.

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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