Interaction of Statistics and Geometry: A New Landscape for Data Science
- 2025-07-09 (Wed.), 10:30 AM
- Auditorium, B1F, Institute of Statistical Science；The tea reception will be held at 10:10.
- Online live streaming through Microsoft Teams will be available.
- Prof. Zhigang Yao
- Department of Statistics and Data Science, National University of Singapore
Abstract
The community studying the connection between statistics and geometry is growing rapidly in both size and scope. The idea of manifold fitting dates back to H. Whitney’s work in the early 1930s. The Whitney extension problem has led to new approaches for data interpolation and inspired a set of questions now known as the Geometric Whitney Problems. One key question is: given a set of data, when can we find a smooth $d$-dimensional surface (or manifold) that approximates it well, and how accurately can we measure that fit in terms of distance and smoothness? In this talk, I will give an overview of the manifold fitting problem and discuss some recent insights and developments. I will focus on an application in NMR-based metabolomics, where we use manifold fitting to study metabolic variation in the UK Biobank population. The discussion will draw on recent work by Yao, Yau, and collaborators, as well as ongoing research.
Please click here for participating the talk online.
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