Urbana, IL 61801
- Ecological economics
- Sustainability science
- High performance geospatial computing
My research interests are in the general area of sustainability science, GeoAI, and big data. I am interested in developing multi-source data model to assess socioeconomic development in less developed regions. I am also interested in developing deep learning and machine learning algorithmic optimizations and utilizing cutting-edge computing technologies for efficient geospatial big data analytics.
- PhD - University of Denver
- MS - University of Pennsylvania
- BS - University of California, Berkeley
- High Performance Geospatial Computing
- Spatial Problem Solving
- GeoAI and Machine Learning
Wang, X*., Li, J., & Zhang, T. (2020). Building a GPU-Enabled Analytical Workflow for Maritime Pattern Discovery Using Automatic Identification System Data. In High Performance Computing for Geospatial Applications (pp. 227-248). Springer.
Qi, B., Wang, X*., & Sutton, P. (2021). Can nighttime satellite imagery inform our understanding of education inequality?. Remote Sensing, 13(5), 843.
Li, J*., Wang, X., & Zhang, T. (2021). Sequence-based centrality measures in maritime transportation networks. IET Intelligent Transport Systems.
Wang, X*., Rafa, M., Moyer, J. D., Li, J., Scheer, J., & Sutton, P. (2019). Estimation and Mapping of Sub-National GDP in Uganda Using NPP-VIIRS Imagery. Remote Sensing, 11(2), 163.
Wang, X., Li, J*., & Zhang, T. (2019). A Machine-Learning Model for Zonal Ship Flow Prediction Using AIS Data: A Case Study in the South Atlantic States Region. Journal of Marine Science and Engineering, 7(12), 463.
Wang, X*., Sutton, P. C., & Qi, B. (2019). Global Mapping of GDP at 1 km2 Using VIIRS Nighttime Satellite Imagery. ISPRS International Journal of Geo-Information, 8(12), 580.