Gillian Grindstaff

Gillian Grindstaff is a Research Fellow at the Mathematical Institute, University of Oxford, within the Department of MATH. Her research interests include geometric and topological data analysis, with a focus on applications in various scientific domains. Grindstaff is affiliated with the Machine Learning and Data Science research group and the Oxford Centre for Industrial and Applied Mathematics. She is also associated with the Topological Data Analysis subgroup. Her recent publications include work on intrinsic bottleneck distance for merge trees, topological classification of tumour-immune interactions, and automated earthwork detection using topological persistence.

Gillian Grindstaff is a researcher at Oxford University with expertise in phylogenetics, metric geometry, and topological data analysis. Her work explores the geometric and topological structures underlying biological and data-driven systems. Grindstaff's research includes the application of topological data analysis to spatial systems, such as polling-place and public-park accessibility, and the development of frameworks for analyzing access to resources with heterogeneous quality. She also investigates phylogenetic tree spaces, including their isometry groups and co-phylogenetic structures. Her contributions span both theoretical and applied aspects, with a focus on improving the assessment of medical conditions through topological methods and enhancing the understanding of complex data through geometric modeling.