Our Research

The geolab seeks to empower the disempowered by increasing the diversity of those that can participate in data-driven decisionmaking. We do this by providing free access to critical "building block" datasets and technologies, engaging in applied and basic research at the intersection between artificial intelligence and big data, and training the next generation of leaders in the use of data for decisionmaking activities.

Recent Peer Reviewed Academic Publications

News & Analysis

All Publications

Partnerships & Programs

The geoLab has partnered with a wide range of external partners to enable our students to gain real-world experience while still at William & Mary.  To date, groups that have provided us with funding or other material include:

Tearline.mil (National Geospatial Intelligence Agency). GeoLab is a long-term partner of NGA's Tearline Program. Since 2020, GeoLab has published Tearline articles on topics such as China's Belt Road investments globally, environmental impacts in Ukraine, and Russian influence in Africa. GeoLab also provides joint project support to newer Tearline partners so they may benefit from GeoLab's institutional knowledge with NGA's Tearline Program. 

GRID3. Students have worked with the GRID3 program to help identify and delineate healthcare catchment areas on the African continent.  We continue to work closely with GRID3 in order to facilitate the identification of administrative boundaries in similar locations.

Commonwealth Cyber Initiative (CCI). Students have worked with external practitioners from a wide range of federal and other agencies to explore topics at the nexus of cybersecurity and satellite imagery.

Global Environment Facility (GEF). This project focuses on better understanding the efficacy of climate related activities implemented by the Global Environment Facility across the entire world.  Students participate by identifying the locations of interventions, metadata about these interventions, and modeling the effects of these interventions using python and R-based code.

United States Department of Homeland Security (DHS). This project focuses on implementing deep learning models to better understand and predict migratory flows to the southern border of the United States.  Students are expected to collect census information, implement existing models, and detail findings of their analyses in public forums. 

National Science Foundation (NSF). The NSF is the core sponsor of the geoboundaries.org project, ensuring access to critical baseline information on geographic boundaries is available to everyone.