Xiaojun Yu

2.6k citations
131 papers · 1.9k · h-index 22

Impact in

Papers in

Xiaojun Yu

116 papers receiving 1.8k citations

Peers

Xiaojun Yu
Comparison fields: 5 of 133
  • Cognitive Neuroscience 704
  • Biophysics 135
  • Human-Computer Interaction 122
  • Signal Processing 213
  • Cellular and Molecular Neuroscience 207
Replace Humaira Nisar with:
Humaira Nisar Malaysia
Dan Liu China
Wenwei Yu Japan
Guozheng Yan China
Uğur Halıcı Türkiye
Ji‐Woong Choi South Korea
Ying Sun China
Kai Ma China
Muhammad Tariq Sadiq China
Xiaojun Yu relative to Humaira Nisar Malaysia Humaira Nisar's profile →
Citations per field
00.5×4.1×
Humaira Nisar · 1×
Citations per year

Countries citing papers authored by Xiaojun Yu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaojun Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019157
2 2019125
3 2020105
4 202089
5 202185
6 201983
7 202283
8 202183
9 202055
10 202047
11 202147
12 202046
13 201439
14 202435
15 201534
16 202134
17 202026
18 202426
19 201725
20 201825

About Xiaojun Yu

Xiaojun Yu is a scholar working on Biomedical Engineering, Cognitive Neuroscience, Electrical and Electronic Engineering, Control and Systems Engineering and Biophysics, having authored 131 papers that have together received 1.9k indexed citations. Recurring topics across this work include Optical Coherence Tomography Applications (38 papers), EEG and Brain-Computer Interfaces (23 papers), Photoacoustic and Ultrasonic Imaging (19 papers), Advanced Fluorescence Microscopy Techniques (11 papers), Blind Source Separation Techniques (11 papers), Neuroscience and Neural Engineering (10 papers), Retinal Imaging and Analysis (6 papers) and Image and Signal Denoising Methods (5 papers). The work is most often cited by research in Cognitive Neuroscience (704 citations), Biophysics (135 citations), Human-Computer Interaction (122 citations), Signal Processing (213 citations) and Cellular and Molecular Neuroscience (207 citations). Xiaojun Yu has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Muhammad Tariq Sadiq, Zhaohui Yuan, Muhammad Zulkifal Aziz, Zeming Fan, Gaoxi Xiao, Linbo Liu, Ateeq Ur Rehman, Guoqi Li, Weiping Ding and Yuekuan Zhou. Their work appears in journals such as IEEE Access, Biomedical Signal Processing and Control, Sensors, Optics Express and Laser 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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