I am a geographic information scientist with听broad training in geography, statistics, computer science and earth sciences. Prior to joining CU, I spent several years teaching in the Department of Geosciences at Texas Tech University where I also served as the director of the Center for Geospatial Technology. I have a PhD in Geography and a Master's degree听in Applied Probability and Statistics from the University of California, Santa Barbara. I did my postdoc training at听the University of Illinois Urbana-Champaign (Geography Department and National Center for Supercomputing Applications). I did my undergraduate (Earth Sciences and Computer Science) in Zhejiang University back in China, and before moving back to academia I also spent several years in industry.
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 is听deep 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 develop听methods and tools to address the computing challenges听that 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.
I am very fortunate and excited to join the family of the 麻豆免费版下载Geography, the world-renowned听geography program, and very excited to explore collaborative opportunities with colleagues within the department and across the 麻豆免费版下载campus. After spending several years in the Texas high plains, I am also very excited about the wonderful geography, landscape and weather variations in the Rockies.