Diversification and complication of information are creating problems that cannot be solved by any single existing academic field. In response to that, this course at the forefront of data science studies formulates a new methodology of data science dealing with culture, beyond the frameworks of mathematics, information and statistics and based on the knowledge accumulated in the respective fields.
- Advanced Lectures in Numerical Analysis
- Advanced Lectures in Mathematical Modeling
- Advanced Lectures in Mathematical Statistics
- Advanced Lectures in Multivariate Analysis
- Advanced Lectures in Mathematical Foundation
- Advanced Lectures in Mathematical Sciences
- Advanced Lectures in Information Access Technologies
- Advanced Lectures in Database Systems
- Advanced Lectures in Biostatistics
- Advanced Lectures in Principles of Statistical Consulting
- Advanced Lectures in Time Series Analysis
- Advanced Lectures in Digital Signal Processing
- Advanced Lectures in Algorithms
- Advanced Lectures in Mathematical Optimization
- Extensive Lectures in Mathematical Modeling 1
- Extensive Lectures in Mathematical Modeling 2
- Extensive Lectures in Relational Data Analysis
- Extensive Lectures in Large Data Analysis
- Extensive Lectures in Mathematical Foundation
- Extensive Lectures in Mathematical Sciences
Thesis Title Examples
- Possibility of Penetration of Rabies into Hokkaido‐A Study with a Mathematical Model
- Research on the Decision of Information Unit for Understanding Document Content
- Understanding and Comparing Characteristics of Soccer Teams Using Sequentially Recorded Data
- Research on the Similarity Calculation Method for Complex Data
- Basic Research on Culture and Information Science and Ideal Types Modeling Analysis‐Concepts and Methods in Culture and Information Science‐
data engineering, Internet information science, library and information science
Development of technology for effective storage, search and use of big data
Today’s advanced information society is not only seeing overflow of data but also its complexity. People solve various problems by collecting information from such data and acquiring new knowledge through using them. I teach students the skill to store, search and use appropriate data for solving the problems they deal with.
Theoretical characterization of multivariate data analysis methods and development of a new method
My research interests include multivariate data analysis methods, social network analysis, sports data analysis, matrix decomposition-type multivariate analysis methods and symbolic data analysis methods. I teach students the theory and application of various methods of multivariate data analyses and provide them with the practical problem-solving skill using statistical science.
mathematical statistics, econometrics
Development of statistical theory in multivariate models and its application to practical problems.
My current research interest is theory of statistical inference of network structures in high-dimensional models, such as graphical models, social network models and structural equation models. Recently I am especially interested in inference of causal structure of social phenomena. Further, I also work on the application of these theories to practical problems.