Lillian Petersen analyzes large data sets to answer relevant questions. She learned python programming in fifth grade and has completed a different research project every year since seventh grade. She is fluent in python, C++, unix, vim, git, latex, shell script, R, and google cloud computing. She has two single-author papers in the peer-reviewed journals Remote Sensing and MDPI Climate.
In 10th grade, Petersen created an early warning system to predict crop yields in every African country 3-4 months before the harvest. For this work, she was invited to give hour-long seminars at USAID, IFPRI, USDA, GEOGLAM, FEWS NET, and UCSD, and was an invited oral presenter at the conferences AGU, Geo4Dev, and the CGIAR Big Data in Agriculture Conventions. In 2020, she won first place in the Regeneron Science Talent Search, a science and math competition for high school seniors, with a scientific model that is able to accurately predict crop harvests and thus reduce food insecurity.
Petersen is now an undergraduate student at Harvard pursuing a degree in Applied Math and Molecular Biology.
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