Research interests:

Jing’s research interests cover a wide range of areas in geographic information science, including spatial analysis, spatial statistics, spatial modeling, and spatial optimization, etc. Currently, she focuses on developing quantitative methods for spatially integrated analysis and modeling and particularly their applications in social science and health research. Also, she is interested in spatial optimization and decision making, including facility location modeling, regionalization and land use optimization.

-Geographical Information Science

-Spatial Statistics

-Spatial Optimization

-Location Modeling

-Health Geography

-Regional Science

-Urban and Regional Planning and development

Career history:

Present: Lecturer in Urban Big Data and Quantative Methods (Urban Studies)

Dr Jing Yao joined University of Glasgow as a lecturer in Urban Big Data and Quantitative Methods at the UK ESRC-funded Urban Big Data Centre in October, 2014. She has a PhD in Geography and a MSc in Industrial Engineering both from Arizona State University (ASU), USA. She also has a MSc degree and a BSc degree in Geographical Information System (GIS) from Nanjing University, China. Previously she worked as a postdoctoral associate at GeoDa Center for Geospatial Analysis and Computation at ASU in the US and a research fellow at Centre for Geoinformatics at University of St Andrews in UK.

Active research projects:

The Re-Making of Chinese Urban Neighbourhoods: Socio-Spatial Transformation and Access to Public Services. Funded by ESRC. Co-Investigator. 2016-2019.

Glasgow-Nankai Research Exchange Grant. 2015.

Spatial Optimization Approaches for Solving the Continuous multi‐Weber Problem. Funded by

National Natural Science Foundation of China. Principal Investigator. 2013-2015.

Continuous Geographic Physical Process Model and its Integration with GIS. Funded by National Natural Science Foundation of China. Co-Investigator. 2013-2015.

Recent publications:

Yao, J., and Fotheringham, A. S. (2016) Local spatiotemporal modeling of house prices: a mixed model approach. Professional Geographer, 68(2), pp. 189-201. (doi:10.1080/00330124.2015.1033671)

Fotheringham, A. S., Crespo, R., and Yao, J. (2015) Geographical and temporal weighted regression (GTWR). Geographical Analysis, 47(4), pp. 431-452. (doi:10.1111/gean.12071)

Agadjanian, V., Hayford, S. R., Luz, L., and Yao, J. (2015) Bridging user and provider perspectives: Family planning access and utilization in rural Mozambique. International Journal of Gynecology and Obstetrics, 130(Supl 3), E47-E51. (doi:10.1016/j.ijgo.2015.03.019) (In Press)

Fotheringham, A.S., Crespo, R., and Yao, J. (2015) Exploring, modelling and predicting spatiotemporal variations in house prices. Annals of Regional Science, 54(2), pp. 417-436. (doi:10.1007/s00168-015-0660-6)

Yao, J., and Murray, A. T. (2014) Serving regional demand in facility location. Papers in Regional Science, 93(3), pp. 643-662. (doi:10.1111/pirs.12013)