Name: Zengyun Hu, Professor, National Youth Talent

Email: hzyhjq@sjtu.edu.cn

Office Tel: 021-776975

Research Interest:  

Public Health, Disease Models, Infectious Disease Prediction and Early Warning, Extreme Climate Events, Risk Assessment Modeling, Artificial Intelligence, Big Data, and the impact of environmental changes on human health.

Dr. Zengyun Hu is the professor of School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine. He graduated with the Ph D in Applied Mathematics, and has been engaged in the long-term interdisciplinary research of Environmental Change and Human Health for more than 15 years. Until now, the applicant has published 80 papers (peer-reviewed) in SCI journals, including 45 papers as the first author/corresponding author. As PI, he has hosted 10 projects supported by the Chinese Academy of Sciences and the National Natural Science Foundation of China (NSFC). He also has hosted more than 20 projects as Co-PI supported by NSFC.

Because of his excellent academic records, he has acted as reviewer for many SCI journals, such as Journal of Travel Medicine, One Health, Hydrology and Earth System Sciences; Earth’s Future; Journal of Hydrology. Now, he has been served as the editor of Science in One Health, One Health Bulletin, and Associate Editor in Frontiers in Environmental Science and the Guest Editor in Acta Tropica.

Professor Hu’s major Academic Contributions include

(1)According to the Da Dao Zhi Jian, based on the Euclidean distance, originally constructing the CCHZ-DISO system successfully solving the comprehensive evaluation, ranking, and clustering. CCHZ-DISO can be applied in Diverse Scientific Domains and has more advantages than traditional systems.  

(2)Establishing the PTPLS interpolation system, which can be widely used in the big data spatiotemporal interpolation of different research areas.

(3)Solving the relationships between the roots of cubic equation and 1, which is the mode transition theory for 3-dimension complex system.

(4)Developing new technologies for infectious disease prediction and early warning modeling and prevention and control by integrating multiple disciplines, such as public health, applied mathematics, geography, big data and artificial intelligence.

The Selected Publications

1.Cui, Q., Shi, Z., Hu, Z., Yimamaidi, Z., Hu, B., Zhang, Z., Saqib, M., Zohaib, A., Gulnara, B., Yersyn, M., Lil, S., 2023, Dynamical variations of the COVID-19 with the SARS-CoV-2 Omicron of Kazakhstan and Pakistan. Infectious Diseases of Poverty. 12: 18.

2.Wang, X., Yin, G., Hu, Z., He, D., Cui, Q., Feng, X., Teng, Z., Hu, Q., Li, J., Zhou, Q., 2021, Dynamical variations of the Global COVID-19 Pandemic based on a SEICR disease model: a new approach of Yi Hua Jie Mu, GeoHealth, 5, 2021GH000455.

3.Cui, Q., Hu, Z., Han, J., Li, Y., Han, J., Teng, Z., Qian, J., 2020, Dynamic variations of the COVID-19 disease at different quarantine strategies in Wuhan and mainland China, Journal of Infection and Public Health, 13, 849-855.

4.Hu, Z., Cui, Q., Han, J., Wang, X., Sha, W., Teng, Z., 2020, Evaluation and prediction of the COVID-19 variations at different input population and quarantine strategies, a case study in Guangdong province, China, International Journal of Infectious Disease, 95, 231-240.

5.Hu, Z., Teng, Z., Zhang, T., Zhou, Q., Chen, X., 2017，Globally asymptotically stable analysis in a discrete time eco-epidemiological system, Chaos, Solitons & Fractals, 99, 20-31.  

6.Hu, Z., Chang, L., Teng, Z., 2016, Bifurcation analysis of a discrete SIRS epidemic model with standard incidence rate. Advances in Difference Equations, 2016:155.

7.Hu, Z., Teng, Z., Jia, C., Zhang, C., Zhang, L., 2014, Dynamical analysis and chaos control of a discrete SIS epidemic model, Advances in Difference Equations, 2014:58.

8.Hu, Z., Teng, Z., Zhang, L., 2014, Stability and bifurcation analysis in a discrete SIR epidemic model. Mathematics and Computers in Simulation, 97, 80-93.

9.Hu, Z., Teng, Z., Jiang, H., 2012, Stability analysis in a class of discrete SIRS epidemic models. Nonlinear Analysis: Real World Application, 13, 2017-2033. ESI High Citied.

10.Hu, Z., Teng, Z., Zhang, L., 2011, Stability and bifurcation analysis of a discrete predator-prey model with nonmonotonic functional response. Nonlinear Analysis: Real World Applications, 12, 2356-2377.

11.Hu, Z., Chen, D., Chen, X., 2022, CCHZ-DISO: A Timely New Assessment System for data quality or model performance from Da Dao Zhi Jian, Geophysical Research Letters, 49, e2022GL100681.

12.Hu, Z., Chen, X., Zhou, Q., Yin, G., Liu, J., 2022, Dynamical variations of the terrestrial water cycle components and the influences of the climate factors over the Aral Sea Basin through multiple datasets, Journal of Hydrology, 604: 127270.

13.Hu, Z., Zhang, Z., Sang, Y., Qian, J., Feng, W., Chen, X., Zhou, Q., 2021, Temporal and spatial variations in the terrestrial water storage across Central Asia based on multiple satellite datasets and global hydrological models, Journal of Hydrology, 596, 126013.  

14.Zhou, Q., Chen, D., Hu, Z*., Chen, X*, 2021, Decompositions of Taylor diagram and DISO performance criteria, International Journal of Climatology, 41 (12), 5726-5732.ESI High Citied.

15.Hu, Z., Chen, X., Zhou, Q., Chen, D., Li, J., 2019, DISO: A rethink of Taylor diagram, International Journal of Climatology, 39, 2825-2832.

16.Hu, Z., Chen, X., Chen, D., Li, j., Wang, S., Zhou, Q., Yin, G., Guo, M., 2019, “Dry gets drier, wet gets wetter”: A case study over the arid regions of central Asia, International Journal of Climatology, 39, 1072-1091.

17.Hu, Z., Zhou, Q., Chen, X., Li, J., Li, Q., Chen, D., Liu, W., Yin, G., 2018, Evaluation of three global gridded precipitation data sets in central Asia based on rain gauge observations, International Journal of Climatology, 9, 3475-3493.

18.Hu, Z., Zhou, Q., Chen, X., Qian, C., Wang, S., Li, J., 2017, Variations and changes of annual precipitation in Central Asia over the last century, International Journal of Climatology, 37,157-170.

19.Hu, Z., Hu, Q., Zhang, C., Chen, X., Li, Q., 2016, Evaluation of reanalysis, spatially interpolated and satellite remotely sensed precipitation data sets in central Asia, Journal of Geophysical Research: Atmospheres, 121, 5648-5663.

20.Hu, Z., Zhang, C., Hu, Q., Tian, H., 2014, Temperature Changes in Central Asia from 1979 to 2011 Based on Multiple Datasets, Journal of Climate, 27, 1143-1167. ESI High Citied.