Amin studies applied economics, statistics, and data science with a focus on agriculture, industrial organization, energy, and resources.
In her paper, Amin used machine learning with national census data to predict food deserts, which have no grocery stores with healthful options, as well as ‘food swamps,’ which have an excess of less healthful foods, such as fast food restaurants, in relation to grocery stores. She found that education, income, population density, and race are strong predictors of the retail food environment; Black population is an important predictor of both food deserts and swamps. Food swamps suffer more from poverty, inequality, and transportation problems, while food deserts are more likely to be rural areas.
Her model helps shed light on the different nutritional challenges that diverse U.S. communities face and shows that they require different approaches to solve.
“My research shows that it’s possible to make more informed decisions on existing social problems, when approached with machine learning and artificial intelligence,” Amin said.
The competition was created by the Committee on the Opportunities and Status of Blacks in Agricultural Economics (COSBAE) and the Committee on Women in Agricultural Economics (CWAE) to help link students, post-doctoral associates, and early-career faculty with mentors at land-grant institutions, agencies, and industry.
The competition committee unanimously recommended Amin’s research report for the first-place award.
“The committee’s recognition encourages me and many other scientists in the field to investigate the issues from a modern, data-driven angle,” she said. “It inspires me to do more exciting research in the future, and helps to expand my network for interdisciplinary collaboration.”
Amin graduated in May, and is now a tenure-track assistant professor at Texas Tech University. She was advised at WSU by Regents Professor Jill McCluskey.