Ying Zhu
- Developmental Neuroscience top 10%
- Neurology top 10%
- Genetics top 10%
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- Cardiovascular Health and Disease Prevention 14
- Heart Rate Variability and Autonomic Control 5
- Cardiovascular Function and Risk Factors 5
- Blood Pressure and Hypertension Studies 5
- Modeling and Simulation top 5%
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- Cerebrovascular and Carotid Artery Diseases 5
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- Complex Systems and Time Series Analysis 5
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- Uterine Myomas and Treatments 5
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- Fetal and Pediatric Neurological Disorders 4
Ying Zhu
91 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 128
- Developmental Neuroscience 65
- Neurology 120
- Genetics 148
- Cardiology and Cardiovascular Medicine 220
- Modeling and Simulation 43
Countries citing papers authored by Ying Zhu
This map shows the geographic impact of Ying Zhu'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 Ying Zhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Zhu more than expected).
Fields of papers citing papers by Ying Zhu
This network shows the impact of papers produced by Ying Zhu. 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 Ying Zhu. The network helps show where Ying Zhu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ying Zhu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 6 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 5 | |
| 7 | 2024 | 2 | |
| 8 | 2023 | 6 | |
| 9 | 2021 | 1 | |
| 10 | 2020 | 5 | |
| 11 | 2019 | 32 | |
| 12 | 2019 | 32 | |
| 13 | 2017 | 2 | |
| 14 | 2017 | 19 | |
| 15 | [Association between blood pressure level and incidence of carotid artery plaque in middle-aged and elderly people]. | 2013 | 1 |
| 16 | 2010 | 1 | |
| 17 | 2009 | 1 | |
| 18 | 2009 | 1 | |
| 19 | 2005 | 16 | |
| 20 | 2005 | 1 |
About Ying Zhu
Ying Zhu is a scholar working on Cardiology and Cardiovascular Medicine, Obstetrics and Gynecology, Neurology, Rheumatology and Pediatrics, Perinatology and Child Health, having authored 101 papers that have together received 1.5k indexed citations. Recurring topics across this work include Cardiovascular Health and Disease Prevention (14 papers), Heart Rate Variability and Autonomic Control (5 papers), Cerebrovascular and Carotid Artery Diseases (5 papers), Cardiovascular Function and Risk Factors (5 papers), Blood Pressure and Hypertension Studies (5 papers), Complex Systems and Time Series Analysis (5 papers), Uterine Myomas and Treatments (5 papers) and Fetal and Pediatric Neurological Disorders (4 papers). The work is most often cited by research in Developmental Neuroscience (65 citations), Neurology (120 citations), Genetics (148 citations), Cardiology and Cardiovascular Medicine (220 citations) and Modeling and Simulation (43 citations). Ying Zhu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Fang Yang, Ruimin Wang, Jingyi Tu, Darrell W. Brann, Quanguang Zhang, Yongbin Wang, Shengkui Zhang, Chunjie Xu, Juxiang Yuan and John K-J. Li. Their work appears in journals such as Scientific Reports, Frontiers in Neurology, International Journal of Surgery, PLoS ONE and Horticulturae.
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.