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.
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.
Theoretical analyses of algorithms and their practical implementation.
My research interests focus on the theory of algorithms and computational complexity of mathematically formalized problems, in particular, combinatorial optimization problems such as tree pattern matching and graph data mining. Currently I am also interested in how to easily integrate such theoretical formalization, or models, with empirical knowledge and techniques. I teach students how to evaluate, improve, and renovate algorithms and how to realize them into a running software.
Statistical Science, Statistical Physics
Formulation of research methods in scientific fields from a statistical perspective
The purpose of my research is to develop statistical methods to extract necessary information and remove noise from measured data, mainly in the field of physics, and offer such methods to researchers. I aim to establish scientific methodologies to replace the conventional approach, which depends on the intuition and experience of researchers, so that anyone, whether specialist or otherwise, can engage in research activities.
Complex Systems, Mathematical Biology, Network Science
Using quantitative data and mathematical models to study complex systems
Things that consist of various elements working together are called “systems.” In my research, I combine mathematical models and quantitative data to understand a range of systems from theoretical and experimental standpoints. Elucidating the laws underlying systems will enable us to reach a deeper understanding of human beings and society, potentially enabling us to predict conditions in the future and control these conditions to be more favorable.