Doctor of Functional Mathematics
Statistical Science, Machine Learning
We are developing practical methods for multivariate analysis that takes the covariance structures into consideration, such as factor analysis, structural equation modeling, graphical models, and canonical discriminant analysis. Specifically, we propose a new method based on structural regularization and clustering based on prediction, develop several numerical algorithms that efficiently compute the estimate of the parameter, and investigate theoretical properties of the estimated parameters. Most of the proposed methods are available for use in the R packages. Also, I have been working on applied statistics, such as electricity demand forecasting and material properties prediction.
Educational Activities
I am in charge of School of Interdisciplinary Science and Innovation, Department of Mathematics, Graduate School of Mathematics, and Joint Graduate School of Mathematics for Innovation. Educational activities are conducted through lectures and seminars.
Professional and Outreach Activities
Through joint research with companies and participation in FMfI and SGW, I have developed several statistical methods that can be used for real problems. I have accomplished the social implementation of COI project..