Yasuaki Hiraoka (Ph.D.)
Title
Team Leader
Introduction
[CLOSED]
Topological data analysis (TDA) is an emerging concept of data analysis for characterizing shape of data. In particular, it provides a tool called the persistent homology that extracts multiscale topological features embedded in data. Our team studies theory and algorithm on persistent homology based on representation theory, probability theory, machine learnings, and inverse problems. We also apply TDA into scientific and engineering problems such as materials science, life and medical science, meteorology, and economics.
Main Research Field
Mathematics
Research Field
Materials Sciences / Computer Science / Multidisciplinary
Research Subjects
Topological Data Analysis
Persistent Homology
Persistent Homology
Laboratory Website URL
Introduction Video
Poster(s)
- FY2019 Research Results (Japanese version)
- FY2018 Research Results (Japanese version)
Related posts
posted on October 22, 2020 16:54Seminar
posted on June 22, 2020 16:28Award
posted on March 19, 2018 14:54Information
