Hidetoshi Shimodaira
Hidetoshi Shimodaira (Ph.D.)
Team Leader


  • Team leader
    Hidetoshi Shimodaira
  • Postdoctoral researcher
    Thong Pham
  • Visiting scientist
    Akifumi Okuno
  • Visiting scientist
    Tomoharu Iwata
  • Visiting scientist
    Junya Honda
  • Visiting scientist
    Shinpei Imori
  • Visiting scientist
    Yoshikazu Terada
  • Visiting scientist
    Sho Yokoi
  • Junior research associate
    Masaaki Inoue
  • Part-time worker I
    Kenta Kihara
  • Part-time worker I
    Hiroaki Yamagiwa
  • Part-time worker II
    Momose Oyama
  • Part-time worker II
    Ryoma Hashimoto


Laboratory's photo

We pursue the methodology of statistics and machine learning. Statistics has been playing important roles as a theoretical basis for data science and artificial intelligence. It provides the methodology of inductive inference by considering probability. We believe that working on real data analysis will lead to the development of theory and methods of statistics. We developed a method of statistical hypothesis testing (multiscale bootstrap) which is now commonly used for DNA sequence analysis and gene expression analysis. We also developed a theory of information criterion for the transfer learning (covariate shift) of machine learning. Recently, we are also working on statistical inference of the growth mechanism of complex networks, and multivariate analysis methods and their deep learning for integrating several types of data such as images and sentences.

Main Research Field
Computer Science
Research Field
Molecular Biology & Genetics / Mathematics
Research Subjects
Machine Learning
Laboratory Website URL

Introduction Video

Mathematical Statistics Team (PI: Hidetoshi Shimodaira) thumbnails

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