Introducing Guofeng Cao
![Guofeng Cao](/geography/sites/default/files/styles/medium_750px_50_display_size_/public/article-image/guofeng_cao_headshot.jpg?itok=LZlKZ9f2)
My research is characterized by an interdisciplinary perspective on geographic information science driven by the advances of spatial Big Data (e.g., social media and remote sensing), machine learning/artificial intelligence, and computational sciences. The overarching goal isÌýdeep learning of heterogeneous geographic information to support uncertainty-aware geographic knowledge discovery and decision making. Particularly, I focus on the development of statistical/machine learning and computational methodologies to integrate heterogeneous sources of geographic information for complex spatiotemporal patterns. I am particularly interested in characterizing and modeling geospatial biases and uncertainty of geographic information and the associated impacts in scientific applications and practical decision making. I also developÌýmethods and tools to address the computing challengesÌýthat arise when the data scales and computation complexity are not manageable with regular computers. I work closely with domain scientists to build geospatial cyberinfrastructure to tackle domain challenges, with a particular focus on natural hazards, environmental sciences, public health and global changes. My research has been supported by several funding agencies, including NSF, USGS, NIST, USAID, USDA and NIH.
![Guofeng Cao in datacenter](/geography/sites/default/files/styles/medium_750px_50_display_size_/public/article-image/guofeng_cao_in_datacenter.jpg?itok=s_l-lisX)