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 and Statistics.
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 the Institute of Mathematics at Technische Universität Berlin and the AI for Society, Science, and Technology Department at the Zuse-Institute Berlin. As an NSF Graduate Research Fellow at North Carolina State University, I was advised by Patrick L. Combettes. 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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