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地理与规划学院任讲师并取得终身教职。2016年度英国经济与社会科学研究理事会(ESRC)定量社会科学 Jon Rasbash Prize获得者，主持和参与多项国家自然科学基金和英国经济社会理事会(ESRC)基金项目，国际和国内知名期刊Environment and Planning B、地理科学编委。
主要研究领域包括时空间多尺度统计模型开发及统计软件开发等定量方法研究，以及经济地理与区域发展等应用研究。已在Annals of the American Association of Geographers, Geographical Analysis, International Journal of Geographical Information Science等地理学国际知名期刊上发表30余篇SSCI论文，开发了HSAR开源R统计软件包。
代表性论文：
1. Dong, G P*, Ma J, Chen MX, Pryce W. (2020). Developing a Locally Adaptive Spatial Multilevel Logistic Model to Analyze Ecological Effects on Health Using Individual Census Records. Annals of the American Association of Geographers 110(3): 739-757.
2. Dong, G P*, Ma J, Harris R and Pryce G. (2016). Spatial Random Slope Multilevel Modelling using Multivariate Conditional Autoregressive Models. Annals of the American Association of Geographers 106(1): 19-35.
3. Dong, G P* and Harris, R. (2015). Spatial Autoregressive Models for Geographically Hierarchical Data Structures. Geographical Analysis 47, 173-191.
4. Dong, G P*, Ma J, Kwan M P & Wang Y. (2018). Multi-level temporal autoregressive modelling of daily activity satisfaction using GPS-integrated activity diary data. International Journal of Geographical Information Science, 32, 2189-2208.
5. Dong, G P*, Wolf L, Alexiou A & Arribas-Bel D. (2019). Inferring neighbourhood quality with property transaction records by using a locally adaptive spatial multi-level model. Computers, Environment and Urban Systems, 79: 118-125.
Guanpeng Dong is a Professor in quantitative human geography at Henan University, Henan Province, and a Research Fellow at Chicago University. He got a BA in Geography (2008) at Henan University, and an MSc in Geography (2011) at the Institute of Geographic Sciences and Natural Resources Research (IGSNRR). Following a PhD in Advanced Quantitative Methods at the University of Bristol’s School of Geographical Sciences, Guanpeng Dong joined the University of Sheffield for one year and a half, and then took a permanent lectureship at University of Liverpool. From 2019, he was appointed as the Director of Spatial Data Science Lab and professor of quantitative human geography at Henan University, Henan Province, China.
Guanpeng was awarded the prestigious Jon Rasbash Prize in Quantitative Social Sciences by the UK’s ESRC in 2016. He is currently on the Editorial Boards of journals including Environment and Planning B, and Scientia Geographica Sinica. He has been awarded several research grants from NSFC and ESRC, as principal investigator and co-investigator.
Guanpeng’s key research interesting lies in developing innovative multi-level spatio-temporal statistical models and applying these advanced methodologies to address important social and environmental issues facing the society. He has published over 30 research articles in leading international geographical journals including Annals of the American Association of Geographers, Geographical Analysis, International Journal of Geographical Information Science, and so on. He also developed a R software package HSAR, implementing a range of spatial multilevel statistical models.
Selected Publications:
1. Dong, G P*, Ma J, Chen MX, Pryce W. (2020). Developing a Locally Adaptive Spatial Multilevel Logistic Model to Analyze Ecological Effects on Health Using Individual Census Records. Annals of the American Association of Geographers 110(3): 739-757.
2. Dong, G P*, Ma J, Harris R and Pryce G. (2016). Spatial Random Slope Multilevel Modelling using Multivariate Conditional Autoregressive Models. Annals of the American Association of Geographers 106(1): 19-35.
3. Dong, G P* and Harris, R. (2015). Spatial Autoregressive Models for Geographically Hierarchical Data Structures. Geographical Analysis 47, 173-191.
4. Dong, G P*, Ma J, Kwan M P & Wang Y. (2018). Multi-level temporal autoregressive modelling of daily activity satisfaction using GPS-integrated activity diary data. International Journal of Geographical Information Science, 32, 2189-2208.
5. Dong, G P*, Wolf L, Alexiou A & Arribas-Bel D. (2019). Inferring neighbourhood quality with property transaction records by using a locally adaptive spatial multi-level model. Computers, Environment and Urban Systems, 79: 118-125.
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