Ding-Yu Fei

1.2k citations
46 papers · 1.0k · h-index 17

Impact in

Papers in

Ding-Yu Fei

45 papers receiving 991 citations

Peers

Ding-Yu Fei
Comparison fields: 5 of 91
  • Cognitive Neuroscience 509
  • Human-Computer Interaction 158
  • Cellular and Molecular Neuroscience 266
  • Cardiology and Cardiovascular Medicine 137
  • Biomedical Engineering 172
Replace Harsimrat Singh with:
Harsimrat Singh United Kingdom
Gaetano D. Gargiulo Australia
Akihiro Ishikawa Japan
Antonio Fratini Italy
David E. Thompson United States
Daniele Esposito Italy
Lucia Rita Quitadamo Italy
Aleksandra Kawala‐Sterniuk Poland
M. Chance Spalding United States
Ding-Yu Fei relative to Harsimrat Singh United Kingdom Harsimrat Singh's profile →
Citations per field
00.5×4.8×
Harsimrat Singh · 1×
Citations per year

Countries citing papers authored by Ding-Yu Fei

Since Specialization
Citations

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

Fields of papers citing papers by Ding-Yu Fei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012205
2 1994155
3 201067
4 200964
5 201744
6 201039
7 201435
8 201434
9 200628
10 200026
11 200825
12 200024
13 201422
14 200321
15 201021
16 200917
17 201517
18 200416
19 200414
20 200913

About Ding-Yu Fei

Ding-Yu Fei is a scholar working on Cognitive Neuroscience, Biomedical Engineering, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine and Radiology, Nuclear Medicine and Imaging, having authored 46 papers that have together received 1.0k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (15 papers), Neuroscience and Neural Engineering (11 papers), Muscle activation and electromyography studies (8 papers), Cardiovascular Health and Disease Prevention (5 papers), Advanced Sensor and Energy Harvesting Materials (4 papers), Ultrasound Imaging and Elastography (4 papers), Sleep and Work-Related Fatigue (3 papers) and Coronary Interventions and Diagnostics (3 papers). The work is most often cited by research in Cognitive Neuroscience (509 citations), Human-Computer Interaction (158 citations), Cellular and Molecular Neuroscience (266 citations), Cardiology and Cardiovascular Medicine (137 citations) and Biomedical Engineering (172 citations). Ding-Yu Fei has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Ou Bai, Dandan Huang, Xuedong Chen, Stanley E. Rittgers, James D. Thomas, Kai Qian, Wenchuan Jia, Peter Lin, Kenneth A. Kraft and Vitalii V. Itskovich. Their work appears in journals such as Clinical Neurophysiology, Telemedicine Journal and e-Health, Journal of Biomechanical Engineering, Computers in Biology and Medicine and Neurorehabilitation.

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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