Lillian Petersen analyzes large data sets to answer socially relevant questions. Her research topics include the effects of climate change on crop yields, climate means and extremes in observational data, tracking deforestation, and weather correlations with El Nino. She pulls her data from historical weather observations, crop yields, climate model data, and satellite imagery, and conducts computations with python on the Google Cloud.
Lillian has a passion for science, math, and computer programming, and dedicates her free time to research projects for science fair competitions. In 2017, she placed third in her category at the Intel International Science and Engineering Fair, and was a finalist at the U.S. DOD National Junior Science and Humanities Symposium. Lillian has a particular interest in evaluating the potential effects of climate change, and their associated social and economic costs. She is currently in the Descartes Labs mentorship program where she is using satellite data to calculate vegetation and water indices, which can be used to classify land types. Her computer programs analyze this satellite data using machine learning algorithms to track deforestation. Lillian’s hobbies include playing the violin, ultimate frisbee, and running in the beautiful mountains of New Mexico.