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Moosmueller, Caroline

Caroline Moosmueller

J. Burton Linker Fellow, Assistant Professor
Phillips Hall 324K

Research Interests

Geometric data analysis, computational optimal transport, numerical analysis and approximation theory, applications in biology and medicine

Professional Background

B.Sc in Mathematics, University of Vienna (Austria), 2010; M.Sc in Mathematics, University of Vienna (Austria), 2013; Ph.D in Technical Mathematics, Graz University of Technology (Austria), 2017; Postdoc at Johns Hopkins University, 2017-2019; Visiting Assistant Professor, University of California, San Diego, 2019-2022; Assistant Professor, University of North Carolina at Chapel Hill, since 2022

Research Synopsis

The focus of my research lies in the development of numerical methods for nonlinear and high-dimensional data analysis. I am particularly interested in algorithms that preserve geometric structure, and I work on optimal transport problems, classification tasks in machine learning, linear and nonlinear approximation, and applications in biology and cancer research.

Representative Publications

Linear optimal transport embedding: provable Wasserstein classification for certain rigid transformations and perturbations
C. Moosmueller, A. Cloninger,
Information and Inference: A Journal of the IMA, 12 (1), 363–389, 2023

Linear Optimal Transport Embedding: Provable Wasserstein classification for certain rigid transformations and perturbations
C. Moosmuller, A. Cloninger,
arXiv, arXiv:2008.09165, 2021

Molecular phenotyping using networks, diffusion, and topology: soft-tissue sarcoma
J. Mathews, M. Pouryahya, C. Moosmueller, I. G. Kevrekidis, J. Deasy, A. Tannenbaum,
Scientific Reports 9, 13982, 2019

C1 analysis of Hermite subdivision schemes on manifolds
C. Moosmueller,
SIAM Journal on Numerical Analysis 54 (5), 3003 – 3031, 2016