Guixing Wei

Guixing Wei
Senior GIS and Spatial Analyst

Overview:

Guixing Wei is the senior GIS and spatial data scientist at S4, Brown University. He holds a PhD degree in Geographic Information Science(GIS) from Texas State University. Guixing's research interests include environmental epidemiology, data mining of social media data (e.g., Twitter, The New York Times), human mobility and travel behavior modeling and the development of geospatial analytical methods. He has published research papers in Computers, Environment and Urban Systems, Annals of GIS and conference proceedings. Prior to joining Brown, Guixing was a lecturer teaching fundamentals of GIS and also a GIS consultant serving the whole Texas State community at Texas State University. His expertise include spatial analysis, data mining, programming, web map development, and spatial database management. 

Current Research:

  • Spatio-temporal Mating Patterns Reflected from NYTimes. This project examines how the mating patterns changes over years (1981-2018), in both spatial and temporal dimensions. Instead of using the traditional census or survey data, ,this project turns to the wedding announcements published on The New York Times. The hypothesis is that the patterns reflected from NYTimes shows a significant difference than the traditional perception. the This is a collaborative work with Prof. Zhenchao Qian (PI). 
  • Assessing Indicators of Chronic Child Under-nutrition using Machine Learning Techniques. The overarching aim of this project is to explore new explanatory variables to chronic child under-nutrition. A large amount of variables have been identified as risk factors in literature, using a prior knowledge or logical deduction. However, the application of ML to explore the risk factors of chronic child under-nutrition in Kenya is scant. This is a collaborative work with Prof. Kevin Mwenda (PI). 
  • Spatial Unevenness and Inequality in Kenya. This is a sub-project under Prof. Michael White's Migration and Health in South Africa Project. Many investigations have taken place to understand the inequality in space through a simple comparison between urban and rural territory. However, we question whether the urban/rural is a geographic container in which phenomena of interest are equally distributed. This work therefore aims to reveal the spatial unevenness and inequality within urban and rural territory. 
  • The Construction of Historical Maps. This is a sub-project of Prof. John Logan's history GIS project, which aims to construct historical maps (1930&1940) through historical city directory data. The city directory data list the streets and associated households. 

Services:

  • Workshops on GIS (proprietary&open-source), spatial analysis, Python, R
  • Consulting on GIS (proprietary&open-source), spatial analysis, geographic data management and web mapping 
[email protected]
Expertise:
Spatial Analysis, GIS, Geographic Data Management, Programming (Python&R), Data Mining