Satellite Data Poisoning Project (SDPP)
As the volume of satellite imagery has increased, so too has our need to use machine learning models to mine that data for meainingful, decision-relevant inf...
What We Do
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.
All Our Projects
Migration and Machine Learning (MML) Project
Core Contribution - Improving our understanding of the highly non-linear impact of climate on human migratory decisions across multiple countries in Latin Am...
Global Education Observatory
The Global Education Observatory focuses on collecting, disseminating, and imputing information about school test scores in underserved environments. Our st...
geoInt
The geoInt project focuses on better understanding the evolution of international actors programs using high resolution satellite imagery. Through qualitati...
Climate Intervention Effectiveness Programme (CIEP)
The Climate Intervention Effectiveness Programme conducts analyses (and collects data) to help better inform global climate change mitigation efforts. CIEP ...
geoBoundaries
Produced and maintained by the William & Mary geoLab since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database is an ...
geoFellows
The geoFellows program has three core goals, focused on increasing the diversity of leaders in the computational sciences:
Deep Learning for Satellite Imagery (DL4SAT)
Deep learning techniques have revolutionized a number of fields, predominantly based on research from the computer vision community. The vast majority of li...