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.
Computational optimal transport
Biology and cancer research
- Data Science Networking Event @ UNCHappening on April 20, 11:30 am – 1:30 pm at Wilson Library. Caroline will give a 3-minutes flash talk, see here for details.
- New paperPreprint of our new paper “Linearized Wasserstein dimensionality reduction with approximation guarantees” is available on the arXiv. This is joint work with Alex Cloninger, Keaton Hamm, and Varun Khurana.
- SIAM SEASCaroline, Shira Faigenbaum (Duke) and Sorin Mitran (UNC Chapel Hill) are organizing a mini-symposium on “Non-linear stochastic data assimilation – theory and applications” at this year’s SIAM SEAS. The meeting will be held at Virginia Tech, March 25-26, 2023.