Mollie Van Gordon

Research Scientist

Mollie Van Gordon

Research Scientist


Mollie Van Gordon is a Research Scientist in the Data, Dynamics, and Analytics group at IDM. Mollie earned her Ph.D. at the University of California, Berkeley in the Geography department with a designated emphasis in Computational Science and Engineering. Her research spanned the fields of climate dynamics, land cover change, remote sensing, machine learning, hydrology, and complex systems. As part of her graduate work, Mollie created a high-resolution land cover dataset for the West African Sahel based on satellite imaging, hand-classified maps, and machine learning techniques. This dataset, and the tool developed to create it, have since been distributed in West Africa for use in food security modeling, climate change adaptation planning, national resource management, and international reporting on forests, agriculture, and carbon stores. Her other graduate research, also based in West Africa, included spatial-temporal pattern recognition and analysis of precipitation trends, as well as systems analysis of small-scale watershed hydrology using information theory. Mollie's undergraduate degree from Barnard College of Columbia University includes training in astronomy, physics, women's studies, and international development studies. Her work experience includes women's and environmental advocacy at the United Nations; water, sanitation, and hygiene global development; and consulting for family planning and climate change adaptation efforts in the West African Sahel. Mollie's research interests include developing data-driven methods with wide-ranging applications; bringing data science methods to data-sparse environments; developing creative solutions to intractable problems; and determining how to ask the right questions.

Biography

Mollie Van Gordon is a Research Scientist in the Data, Dynamics, and Analytics group at IDM. Mollie earned her Ph.D. at the University of California, Berkeley in the Geography department with a designated emphasis in Computational Science and Engineering. Her research spanned the fields of climate dynamics, land cover change, remote sensing, machine learning, hydrology, and complex systems. As part of her graduate work, Mollie created a high-resolution land cover dataset for the West African Sahel based on satellite imaging, hand-classified maps, and machine learning techniques. This dataset, and the tool developed to create it, have since been distributed in West Africa for use in food security modeling, climate change adaptation planning, national resource management, and international reporting on forests, agriculture, and carbon stores. Her other graduate research, also based in West Africa, included spatial-temporal pattern recognition and analysis of precipitation trends, as well as systems analysis of small-scale watershed hydrology using information theory. Mollie's undergraduate degree from Barnard College of Columbia University includes training in astronomy, physics, women's studies, and international development studies. Her work experience includes women's and environmental advocacy at the United Nations; water, sanitation, and hygiene global development; and consulting for family planning and climate change adaptation efforts in the West African Sahel. Mollie's research interests include developing data-driven methods with wide-ranging applications; bringing data science methods to data-sparse environments; developing creative solutions to intractable problems; and determining how to ask the right questions.