Ningzhong Shi
- Modeling and Simulation top 0.1%
- COVID-19 epidemiological studies 18
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- Mathematical and Theoretical Epidemiology and Ecology Models 36
- Genetics top 1%
- Evolution and Genetic Dynamics 23
- Statistics and Probability top 1%
- Statistical Methods and Inference 23
- Statistical Methods and Bayesian Inference 22
- Advanced Statistical Methods and Models 19
- Statistical Methods in Clinical Trials 14
- Mathematical Physics top 5%
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- Psychometric Methodologies and Testing 11
- Co-authors
- Daqing JiangChunyan JiJiajia YuTasawar HayatAhmed AlsaediQingshan YangJian TaoXiaoyue Li
- Journals
- Journal of the American Statistical Association (3 papers)Biometrics (1 paper)Automatica (1 paper)
- Partner nations
- ChinaSaudi ArabiaUnited States
In The Last Decade
Ningzhong Shi
100 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 121
- Modeling and Simulation 1.4k
- Public Health, Environmental and Occupational Health 1.9k
- Genetics 1.2k
- Statistics and Probability 299
- Mathematical Physics 246
Countries citing papers authored by Ningzhong Shi
This map shows the geographic impact of Ningzhong Shi'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 Ningzhong Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ningzhong Shi more than expected).
Fields of papers citing papers by Ningzhong Shi
This network shows the impact of papers produced by Ningzhong Shi. 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 Ningzhong Shi. The network helps show where Ningzhong Shi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ningzhong Shi, 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 | 2020 | 3 | |
| 2 | 2020 | 5 | |
| 3 | 2012 | 17 | |
| 4 | 2011 | 3 | |
| 5 | The Function of Mathematics CAI on Long-distance Teaching | 2011 | 0 |
| 6 | 2011 | 172 | |
| 7 | 2010 | 12 | |
| 8 | 2010 | 79 | |
| 9 | 2009 | 273 | |
| 10 | 2009 | 96 | |
| 11 | 2009 | 15 | |
| 12 | 2008 | 51 | |
| 13 | 2007 | 187 | |
| 14 | 2005 | 19 | |
| 15 | 2005 | 27 | |
| 16 | 2004 | 152 | |
| 17 | 2003 | 14 | |
| 18 | 2002 | 15 | |
| 19 | 1998 | 20 | |
| 20 | 1996 | 2 |
About Ningzhong Shi
Ningzhong Shi is a scholar working on Statistics and Probability, Modeling and Simulation and Management Science and Operations Research, having authored 110 papers that have together received 2.7k indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (36 papers), Statistical Methods and Inference (23 papers), Evolution and Genetic Dynamics (23 papers), Statistical Methods and Bayesian Inference (22 papers), Advanced Statistical Methods and Models (19 papers), COVID-19 epidemiological studies (18 papers), Statistical Methods in Clinical Trials (14 papers) and Psychometric Methodologies and Testing (11 papers). The work is most often cited by research in Modeling and Simulation (1.4k citations), Public Health, Environmental and Occupational Health (1.9k citations) and Genetics (1.2k citations). Ningzhong Shi has collaborated with scholars based in China, Saudi Arabia and United States. Frequent co-authors include Daqing Jiang, Chunyan Ji, Jiajia Yu, Tasawar Hayat, Ahmed Alsaedi, Qingshan Yang, Jian Tao, Xiaoyue Li, Qun Liu and Yanbin Zhao. Their work appears in journals such as Journal of the American Statistical Association, Biometrics and Automatica.
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.