Takahiro Hoshino
Takahiro Hoshino (Ph.D.)
Title
Team Leader

Members

  • Team leader
    Takahiro Hoshino
  • Postdoctoral researcher
    Makoto Nakakita
  • Visiting scientist
    Junichiro Niimi
  • Visiting scientist
    Ryosuke Igari
  • Visiting scientist
    Kazuhiko Shinoda
  • Visiting scientist
    Daisuke Moriwaki
  • Part-time worker I
    Yuta Ota
  • Part-time worker I
    Kei Miyazaki
  • Part-time worker I
    Noriaki Okamoto
  • Part-time worker II
    Taiga Hashimoto
  • Part-time worker II
    Yuta Nagaya
  • Part-time worker II
    Natsuki Masuda
  • Part-time worker II
    Ryohei Emori
  • Part-time worker II
    Takuto Doi

Introduction

Laboratory's photo

In the era of rapid technological innovation and high social and economic uncertainty, government and companies are required to make decisions more quickly than ever. Although various large big-data such as transaction logs and location information, various studies showed that they are not useful for managerial or policy decision making as it is, because the big-data suffer from various biases such as selection bias. This team will develop new data-fusion techniques for various types of datasets including governmental survey data, big-data and macro-level information, to improve accuracy of public statistical information, or to aid investment/managerial decision making. We also investigate new data acquisition methods in business and economic fields which utilize statistical machine learning methods.

Main Research Field
Economics & Business
Research Field
Neuroscience & Behavior / Computer Science / Mathematics / Social Sciences & General
Research Subjects
Development of Data fusion techniques
Development of new data acquisition methods in business and economic fields
Inference with anonymization of big-data in business and economics fields
Laboratory Website URL
RIKEN Website URL

Introduction Video

Business and Economic Information Fusion Analysis Team (PI: Takahiro Hoshino) thumbnails
Poster(s)

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posted on May 11, 2020 13:26Information