Biography

Wei Kang is a Research Scientist at UCR Inland Center for Sustainable Development (ICSD). Her research interests are methodological - spatial statistics/econometrics, as well as empirical - housing, neighborhood change, inequality, growth, and convergence. Her current projects focus on affordable housing and housing policies. She is the core developer of the widely used open-source spatial analysis python library – PySAL.

Interests

  • Housing & Poverty & Inequality
  • Local and Regional Development & Urban Data Science
  • GIScience & Spatial Statistics & Spatial Econometrics

Education

  • PhD in Geography, 2018

    Arizona State University

  • MSc in Cartology and GISystem, 2014

    Peking University

  • BSc in Geographic Information System, 2011

    Wuhan University

Academic Appointment

 
 
 
 
 
 
 
 
 
 

Graduate Research Assistant

School of Geographical Sciences and Urban Planning, Arizona State University

Jan 2015 – Apr 2018 Tempe, Arizona
Participated in the NSF project New Approaches for Spatial Distribution Dynamics.
 
 
 
 
 

Graduate Teaching Assistant

School of Geographical Sciences and Urban Planning, Arizona State University

Aug 2014 – Dec 2014 Tempe, Arizona
Teaching assistant for “GIS 470: Statistics for Geographers”.
 
 
 
 
 

Graduate Research Assistant

Institute of Remote Sensing and GIS, Peking University

Sep 2011 – Jun 2014 Beijing, China
Participated in the project “Application of Temporal GIS to Spatio-Temporal Land & Resources Data Management” funded by Beijing Municipal Bureau of Land and Resources.

Recent Publications

(2020). Spatiotemporal patterns of alcohol outlets and violence: A spatially heterogeneous Markov chain analysis. Environment and Planning B: Urban Analytics and City Science.

PDF DOI

(2020). PySAL and Spatial Statistics Libraries. The Geographic Information Science & Technology Body of Knowledge (3rd Quarter 2020 Edition).

PDF DOI

(2020). When Spatial Analytics Meets Cyberinfrastructure: an Interoperable and Replicable Platform for Online Spatial-Statistical-Visual Analytics. Journal of Geovisualization and Spatial Analysis.

DOI

(2020). Sensitivity of sequence methods in the study of neighborhood change in the United States. Computers, Environment and Urban Systems.

DOI

(2020). `splot` - visual analytics for spatial statistics. Journal of Open Source Software.

PDF DOI

Contact

  • 4135 CHASS Interdisciplinary South, 900 University Ave, Riverside, CA 92521
  • DM Me