Departments of Statistics and Computer Science and the College
Rebecca Willett’s research is focused on machine learning, signal processing, and large-scale data science. In particular, she studies methods of leveraging low-dimensional models in a variety of contexts, including when data are high-dimensional, contain missing entries, are subject to constrained sensing or communication resources, correspond to discrete events, or arise in ill-conditioned inverse problems. This work lies at the intersection of high-dimensional statistics, inverse problems in network science and imaging (including compressed sensing), learning theory, algebraic geometry, optical engineering, nonlinear approximation theory, statistical signal processing, and optimization theory.
She was a recipient of an Air Force Office of Scientific Research Young Investigator Program award and a National Science Foundation CAREER Award. She also served as a member of the 2005–06 Defense Advanced Research Projects Agency Computer Science Study Group.
Willett completed her PhD in electrical and computer engineering at Rice University. Most recently, she was an associate professor of electrical and computer engineering at the University of Wisconsin–Madison, as well as a Harvey D. Spangler Faculty Scholar and a fellow of the Wisconsin Institutes for Discovery. Previously, she was an associate professor of electrical and computer engineering at Duke University.