About me
I research nonsmooth optimization, splitting algorithms, machine learning, and monotone operator theory. My collaborators and I develop these tools to solve nonlinear problems in data science, signal/image/audio processing, and large-scale optimization.
Of particular interest is the development of theoretically-sound practices for data science. I work towards deriving mathematically-precise guarantees of privacy, equity, and optimality.
I am an assistant professor of Applied Mathematics at James Madison University (JMU) in the Department of Mathematics & Statistics. To learn about student research, please check out the lab tab.
Before my current position, I was a postdoctoral researcher working with Sebastian Pokutta at the Interactive Optimization and Learning (IOL) Lab, which is both part of Technische Universität Berlin and Zuse-Institute Berlin. I was advised by Patrick L. Combettes at NC State University on an NSF Graduate Research Fellowship. My PhD thesis was on nonlinear analysis, algorithm development, signal recovery, and modeling. I majored in Mathematics at JMU, and I participated in several undergraduate research programs in the USA with Anne Shiu (Texas A&M), Hala Nelson (JMU), and Caroline Lubert (JMU). On a personal note, I am from the Blue Ridge Mountains of Appalachia. I enjoy cooking, ultimate frisbee, bluegrass, and Dungeons & Dragons.
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