Christine Muthee is the AI and Data Scientist that supports the Yields team in applying Earth Observation data and geospatial AI to accelerate sustainable agricultural productivity across Africa. Her work focuses on building machine learning systems that translate satellite and geospatial data into practical insights for food systems and building climate resilience.

Prior to joining the Food Program, Christine worked as a Machine Learning Research Engineer at École Polytechnique Fédérale de Lausanne, where she contributed to research on evaluating and mitigating bias in AI systems.

Earlier in her career, Christine worked as a Data Analyst in WRI Africa’s Thriving and Resilient Cities pillar, where she supported the delivery of station-level air quality forecasts for 4 African cities by downscaling global atmospheric models such as NASA's GEOS-CF using machine learning and low-cost sensor data.

Christine was also a non-resident fellow with Stimson Center and Microsoft Office of Responsible AI, where she lead discussions on the challenges and opportunities of developing AI for sustainable development.

She holds a BS. in Renewable Energy and Environmental Physics, an Msc. in Engineering Artificial Intelligence from Carnegie Mellon University, and a postgraduate diploma in Data Science and Machine Learning.

Outside work, Christine enjoys, pottery, music and playing chess.