Dan Zhu
- Modeling and Simulation top 10%
- Biophysics top 10%
- Finance top 10%
- Stochastic processes and financial applications 10
- Financial Risk and Volatility Modeling 10
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- Monetary Policy and Economic Impact 9
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- Statistical Methods and Inference 9
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- Insurance, Mortality, Demography, Risk Management 7
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- Probability and Risk Models 5
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- Optical Coherence Tomography Applications 5
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- Market Dynamics and Volatility 5
- Co-authors
- Wei WeiTatsushi OkaMark S. JoshiYang ZhangWeijing QuJiesi WangXinglei ZhuWen Zhang
- Journals
- Astin Bulletin (5 papers)Journal of Econometrics (3 papers)Scandinavian Actuarial Journal (3 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Dan Zhu
75 papers receiving 512 citations
Peers
Comparison fields: 5 of 123
- Biological Psychiatry 22
- Modeling and Simulation 28
- Complementary and alternative medicine 49
- Biophysics 32
- Finance 49
Countries citing papers authored by Dan Zhu
This map shows the geographic impact of Dan 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 Dan Zhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Zhu more than expected).
Fields of papers citing papers by Dan Zhu
This network shows the impact of papers produced by Dan 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 Dan Zhu. The network helps show where Dan Zhu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dan 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 | 1 | |
| 2 | 2024 | 9 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 1 | |
| 9 | 2023 | 9 | |
| 10 | 2023 | 3 | |
| 11 | 2021 | 0 | |
| 12 | 2021 | 4 | |
| 13 | 2020 | 4 | |
| 14 | Effect of baihu ginseng decoction on treatment of type 2 diabetes | 2017 | 1 |
| 15 | Association of probiotics and bone mineral density in Chinese patients with type 2 diabetes | 2017 | 3 |
| 16 | [Multivariate factors analysis on length of stay in Lushan earthquake victims]. | 2014 | 1 |
| 17 | Influence of Cataract Phacoemulsification on Corneal Endothelial Cells in Diabetes | 2013 | 2 |
| 18 | 2012 | 1 | |
| 19 | 2012 | 10 | |
| 20 | 2011 | 3 |
About Dan Zhu
Dan Zhu is a scholar working on Finance, Statistics and Probability and General Economics, Econometrics and Finance, having authored 84 papers that have together received 525 indexed citations. Recurring topics across this work include Stochastic processes and financial applications (10 papers), Financial Risk and Volatility Modeling (10 papers), Monetary Policy and Economic Impact (9 papers), Statistical Methods and Inference (9 papers), Insurance, Mortality, Demography, Risk Management (7 papers), Probability and Risk Models (5 papers), Optical Coherence Tomography Applications (5 papers) and Market Dynamics and Volatility (5 papers). The work is most often cited by research in Biological Psychiatry (22 citations), Modeling and Simulation (28 citations) and Complementary and alternative medicine (49 citations). Dan Zhu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Wei Wei, Tatsushi Oka, Mark S. Joshi, Yang Zhang, Weijing Qu, Jiesi Wang, Xinglei Zhu, Wen Zhang, Kejun Hou and Juan Yuan. Their work appears in journals such as Astin Bulletin, Journal of Econometrics, Scandinavian Actuarial Journal, Insurance Mathematics and Economics and PLoS ONE.
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.