Christine Muthee is an AI engineer and a technical expert in environmental physics and Climate Centered AI technology. She worked a developer in delivering NASA’s GEOS-CF Bias Corrected Forecasts and pollution source insights using satellite data in African cities. This technology preexisting global forecasts, to correct for spatial representation errors and bias in forecasts using machine learning. This tool was translated to produce high-resolution, locally relevant forecasts to influence policies around air quality in African Cities. Her experience in setting up data and AI infrastructure and in Africa has been inherently valuable in scaling down global advancements in technology to suit local needs and bridge the data and technology gap existing in the space.
She has been a vocal advocate for human and nature-focused use of AI as evidenced in panel discussions she has participated in, the Data Science hackathons and communities she coordinates, and the papers she has co-authored. She completed her Masters’s degree in Engineering Artificial Intelligence at Carnegie Mellon University where her research is focused on the development and transfer of Geo-foundation models for downstream environmental tasks. She has a bachelor’s degree in Renewable Energy and Environmental physics from the Technical University of Mombasa, a postgraduate diploma in Data Science and Machine Learning, and a professional certification in Using Data Science for decision-making from the Massachusetts Institute of Technology.