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 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 (AISST) Department at the Zuse-Institute Berlin.

Before my current position, I was a graduate student and NSF Fellow at North Carolina State University, advised by Patrick L. Combettes. My PhD thesis, titled "Construction of Functions from Nonlinear Transformations," was on nonlinear analysis, algorithm development, signal recovery, and modeling. I majored in Mathematics at James Madison University, and I participated in several undergraduate research programs in the USA with Anne Shiu (Texas A&M), Hala Nelson (JMU), and Caroline Lubert (JMU/NASA/Northrop Grumman). 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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my-last-name (at) zib (dot) de

+49 30 841 85 - 563

Zuse Institute Berlin, Room 3107
    Takustr. 7
    14195 Berlin
    Deutschland