Dai Dai
Impact in
- Immunology top 10%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Psoriasis: Treatment and Pathogenesis
- Cognitive Neuroscience top 10%
- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
Papers in
-
- Functional Brain Connectivity Studies 6
- EEG and Brain-Computer Interfaces 2
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- Immune Cell Function and Interaction 5
- T-cell and B-cell Immunology 2
- Co-authors
- Huiguang He (6 shared papers)Nan Shen (12 shared papers)Yikun Yao (1 shared paper)Ju Qiu (1 shared paper)Xinyang Song (1 shared paper)Fangfang Qu (1 shared paper)Honglin Wang (1 shared paper)Xiaoxia Li (1 shared paper)
- Journals
- Arthritis & Rheumatology (3 papers)Frontiers in Pediatrics (1 paper)The Journal of Immunology (1 paper)Arthritis Research & Therapy (1 paper)Lupus Science & Medicine (1 paper)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Dai Dai
22 papers receiving 672 citations
Peers
Comparison fields: 5 of 92
- Immunology 223
- Cognitive Neuroscience 153
- Psychiatry and Mental health 94
- Neurology 45
- Rheumatology 66
Countries citing papers authored by Dai Dai
This map shows the geographic impact of Dai Dai'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 Dai Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dai Dai more than expected).
Fields of papers citing papers by Dai Dai
This network shows the impact of papers produced by Dai Dai. 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 Dai Dai. The network helps show where Dai Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Dai Dai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 189 | |
| 2 | 2012 | 132 | |
| 3 | 2017 | 63 | |
| 4 | 2014 | 53 | |
| 5 | 2012 | 39 | |
| 6 | 2015 | 35 | |
| 7 | 2014 | 28 | |
| 8 | 2020 | 23 | |
| 9 | 2022 | 18 | |
| 10 | 2023 | 17 | |
| 11 | 2022 | 16 | |
| 12 | 2023 | 15 | |
| 13 | 2022 | 15 | |
| 14 | 2011 | 9 | |
| 15 | 2022 | 7 | |
| 16 | 2012 | 7 | |
| 17 | 2020 | 6 | |
| 18 | 2008 | 3 | |
| 19 | 2024 | 2 | |
| 20 | 2018 | 2 |
About Dai Dai
Dai Dai is a scholar working on Cognitive Neuroscience, Immunology, Rheumatology, Radiology, Nuclear Medicine and Imaging and Cancer Research, having authored 24 papers that have together received 681 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (6 papers), Immune Cell Function and Interaction (5 papers), Systemic Lupus Erythematosus Research (4 papers), Advanced Neuroimaging Techniques and Applications (3 papers), T-cell and B-cell Immunology (2 papers), EEG and Brain-Computer Interfaces (2 papers), Retinal Imaging and Analysis (1 paper) and Embedded Systems Design Techniques (1 paper). The work is most often cited by research in Immunology (223 citations), Cognitive Neuroscience (153 citations), Psychiatry and Mental health (94 citations), Neurology (45 citations) and Rheumatology (66 citations). Dai Dai has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Huiguang He, Nan Shen, Yikun Yao, Ju Qiu, Xinyang Song, Fangfang Qu, Honglin Wang, Xiaoxia Li, Shu Zhu and Xiao He. Their work appears in journals such as Arthritis & Rheumatology, Frontiers in Pediatrics, The Journal of Immunology, Arthritis Research & Therapy and Lupus Science & Medicine.
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.