[Taiji Suzuki] Mathematical foundation and methodologies of integrative statistical modeling

Presto Researcher

Taiji Suzuki

Taiji Suzuki

Graduate School of Information Science and Technology, The University of Tokyo
Associate Professor

Outline

This project aims to establish methodologies to enhance a modeling procedure for statistical problems with complicated and various data. Nowadays we are facing a lot of problems for which data science could give a critical solution. That means that there are increasing demands for statistical methodologies, and thus the modeling procedure, the core of statistical methods, is also getting more important. However, statistical modeling is usually carried out for each task independently. In practice, obtaining an appropriate statistical model for a complicated statistical problem is a hard task. To overcome this problem, approaches to unify various tasks are investigated. In particular, hierarchical models and group invariant models are studied from a theoretical point of view. Moreover, we develop an efficient computational methods to execute the proposed methods. By addressing the modeling procedure, we open up a new research paradigm.

Quick Access

Program

  • CREST
  • PRESTO
  • ACT-I
  • ERATO
  • ACT-X
  • ACCEL
  • ALCA
  • RISTEX
  • AIP Network Lab
  • Global Activities
  • Diversity
  • SDGs
  • OSpolicy
  • Yuugu
  • Questions