About

Tomoshiro Ochiai
Professor,
Faculty of Social Information Studies, Otsuma Women’s University,
12 Sanban-cho,Chiyoda-ku,Tokyo 102-8357, Japan,
e-mail: ochiai@otsuma.ac.jp.

Research　Interest

I am engaged in interdisciplinary research across a wide range of fields, from mathematical physics to information science and data science. In particular, I am interested in advancing the field of data science through the development of mathematical and statistical methodologies. My primary focus is on applying these methodologies to various areas such as time series analysis, network science, finance, biology, and medicine, with a strong emphasis on the theoretical aspects of data science. Below are the main themes of my research:

  1. Data Science, Statistics, Complex Systems, Causal Inference: I am researching methodologies for causal inference, such as VC correlation, which estimates the direction of causality from pair data, something not observable through standard correlation coefficients, and studies on directional networks.
  2. Financial Informatics, Econophysics, Financial Engineering: I study data science (data mining) related to finance and economics. In particular, I am focusing on financial analysis, stock and foreign exchange time series analysis, and applications in behavioral economics, using data such as corporate financial information, stock prices, currency rates, and financial transaction histories.
  3. Bioinformatics: With the accumulation of abundant biological and medical data including gene expression and DNA sequencing, I am conducting research on data mining these data from an informatics perspective.
  4. Physics of Invisibility, Cloaking Devices: The feasibility of creating a so-called ‘Harry Potter’ style invisibility cloak has been enhanced with the use of artificial materials known as metamaterials. My research is focused on designing these invisibility cloaks using electromagnetic theory.
  5. Artificial Intelligence, Machine Learning: I am researching the application of artificial intelligence technologies, including deep learning and generative AI, in finance, economics, and biomedicine-related fields.