Presidential fellows Margot Bjoring and Christopher Whitehead are using data science and history to uncover native kinship of indigenous peoples from the Northeast 400 years ago. Through parish records, the two fellows have found names and answered questions of people that otherwise would have gone unnoticed.
Doctoral students Cal Buelo and Neda Nazemi are studying algal blooms and water toxicity using machine learning to understand, and predict them, helping communities better manage water systems and prevent disease.
Cell behaviors and the coordination of those behaviors affect how bacterial communities amass and operate as a population. Jie Wang and Mingxie Zhang are using image data and machine learning to study that behavior.
Researchers Jake Malcomb and Linnea Saby plan to analyze a massive geospatial data set collected over a two-year period from the International Space Station using an “extreme learning machine” tool that aims to mimic the human brain.
New research by a trio of UVA Ph.D. students — two from the University of Virginia Darden School of Business and one from the School of Engineering and Applied Science — is using new data science tools to answer questions related to what makes a job interview successful for both the candidate and the recruiter.
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