SCoDA Workshop: Statistics on Complex Data - Seoul 2026

Session

Keynote

26 Jun 2026, 09:30

Seoul National University

Conveners

Keynote: 1

• Jörn Schulz (University of Stavanger)

Keynote: 2

• Jisu KIM (Seoul National University)

21. Shape Analysis of Dynamic Object Data

Ian Dryden

26/06/2026, 09:30

Object oriented data analysis (OODA) provides a framework for the statistical analysis of a wide variety of highly structured data. Shapes, images, functions, covariance matrices, networks and other manifold-valued data are all examples of object data that can be analyzed using OODA methods. Shapes of 3D objects are a type of manifold-valued data, invariant to translation, rotation and scale....

25. Topological Regularization for Complex Data: Filtration Learning in Exact Multi-Parameter Persistent Homology

Jae-Hun Jung (POSTECH)

27/06/2026, 09:30

Abstract: The shape of complex data -- time series, functional observations, and multimodal measurements -- encodes structural information that classical statistical methods often fail to capture. Topological data analysis addresses this through persistent homology, which tracks the evolution of topological features across a filtration of the data. However, the outcome of any topological...