Every year a number of students are competitively chosen to become geoFellows - individuals who will help lead the lab efforts for the academic year. These students engage heavily in lab leadership, conducting activities that might be relegated to older PIs in other labs such as conducting outreach to funders, interacting with collaborators, and giving presentations to large policy audiences. You can learn more about our fellows and their accomplishments on our achievements page, or learn more about geoFellow research on our research page.
One of the premier data products produced by the geoLab, geoBoundaries is the world's largets open-source collection of administrative boundaries. You can learn more at the geoBoundaries page.
A toolkit to help organizations identify geospatial information within their PDF documents quickly and easily. You can see the most recent version at https://github.com/wmgeolab/geoHighlight .
Working with the World Bank and Global Environment Facility, we have developed techniques to use satellite data and machine learning to identify the impact of environmental initiatives at a global scale. Learn more at the GEF.
In collaboration with a variety of US-based state actors, we are exploring the ability of satellite imagery to detect events of interest to the security community.
Dr. Dan Runfola and Dr. Peter Kemper are exploring the use of Convolutional Neural Networks to detect the location and quality of road infrastructure across the world.