Kyushu University Institute of Mathematics for Industry

IKE, Yuichi

Associate Professor

Researcher Information Research and Technical Catalog

I study topological data analysis and microlocal sheaf theory. Topological data analysis is a field to study the topology of data using various mathematical methods, such as persistent homology. Recently, it has been developed in combination with machine learning. Microlocal sheaf theory is a method to study sheaves on manifolds by analyzing them in cotangent bundles. I am interested in applying this theory to topology and symplectic geometry. I would also like to explore how we can use geometric or algebraic methods in machine learning.

Keywords Topological data analysis, Microlocal sheaf theory, Machine learning
Division Division of Industrial and Mathematical Statistics
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