Welcome!

Left to right: Chuxiangbo Wang, Amartya Banerjee, Aaron Jacobson, Kaitlyn Hohmeier, Caroline Moosmueller, Shiying Li. Picture from September 2024.

We are interested in developing numerical methods for nonlinear and high-dimensional data analysis. Our focus lies on algorithms that preserve geometric structures, and our work includes optimal transport problems, classification tasks in machine learning, linear and nonlinear approximation, and applications in biology and cancer research.

People

Caroline Moosmueller
Shiying Li
Amartya Banerjee
Kaitlyn Hohmeier
Aaron Jacobson
Chuxiangbo Wang
Kwatcho Mahinanda

Research

Computational optimal transport
Approximation theory
Biology and cancer research

  • UNC Data Science Day poster presentations
    Aaron Jacobson Amartya Banerjee Kaitlyn Hohmeier Great turnout of the Geometric Data Analysis group at UNC’s Data Science Day on Sep 26, 2024. Aaron presented his poster on “Spatio-temporal analysis of brain functional connectome”, summarizing his work from last year funded by a Data Science seed grant. He won 3rd place in the poster prize… Continue reading UNC Data Science Day poster presentations
  • Paper on Approximation properties of slice-matching operators
    Shiying’s and Caroline’s paper “Approximation properties of slice-matching operators” is available on the arXiv. In this paper we iterative slicing-and-matching schemes, in particular, the approximation power of one step of such schemes. We show an invariance and an equivariance property with respect to global rigid transformations, approximation of the target measure, and derive a connection… Continue reading Paper on Approximation properties of slice-matching operators
  • Paper on stochastic slicing and matching
    A preprint of Shiying’s and Caroline’s paper “Measure transfer via stochastic slicing and matching” is available on the arXiv. In this paper we discuss an iterative slicing-and-matching procedure which can be used for measure approximation. This scheme has first been introduced by PitiĆ© et. al.; we show a convergence proof of a stochastic version.
  • Data science seed grant
    Caroline, together with Shahar Kovalsky, Martin Styner, and Guorong Wu received a seed grant from the School of Data Science and Society at UNC. Our award on “Spatio-temporal analysis of brain functional connectome” will run until June 2024. Official announcement Abstract: We will develop mathematical models and algorithms for the analysis and statistical characterization of… Continue reading Data science seed grant
  • Data Science Networking Event @ UNC
    Happening on April 20, 11:30 am – 1:30 pm at Wilson Library. Caroline will give a 3-minutes flash talk, see here for details.