Division of Mathematical Science, Department of Systems Innovation, Graduate School of Engineering Science

Mathematical Science is the science in which mathematical and statistical models are constructed, developed mathematically and diagnosed empirically in order to understand practical phenomena which occur in the fields of natural science, social science, technology, biology and so forth.

For the purpose, one needs to utilize computers with advanced levels to make computer simulations, computer graphics and to develop algorithms, among others. In our division, emphasis is placed on research and education of differential equations, mathematical physics, statistical analysis and data science. The mathematical science division consists of two large groups. One is a group of applied mathematics and the other is a group of statistical science, each having two smaller subgroups.

List of Faculty Members

Graduate School DivisionDivision of Mathematical ScienceDivision of Mathematical Science for Social Systems
Course of Study & Name of
Undergraduate Department
Mathematical Science Course,
Department of Information and Computer sciences
Intelligent Systems Science Course,
Department of Systems Science
AreaMathematical ModellingStatistical ScienceMathematical and Statistical FinanceTheoretical Systems Science
Research GroupDifferential
Data Science
Modeling in Finance
Systems Optimization
and Decision Making
ProfessorTakayuki KobayashiMichinori IshiwataJoe SuzukiYutaka KanoMasayuki UchidaJun SekineMasaaki FukasawaToshimitsu UshioMasahiro Inuiguchi
Associate ProfessorSatoshi Masaki Fuyuhiko TanakaSpecially-Appointed Professor: Etsuo Hamada Hidehiro Kaise Takashi MatsubaraNaoki Hayashi
Lecturer Takahiro Okabe Yoshikazu TeradaKosuke Morikawa   
Assistant ProfessorHajime KobaYuusuke Kaino(Concurrent Position in
Kano Lab. & Suzuki Lab.)
Specially-Appointed Assistant Professor: Mariko TakagishiKohei ChibaKei NobaNobuaki NaganumaNaomi KuzeHirosato Seki

Research Groups, Division of Mathematical Science

Area of Mathematical Modelling

In this area, by means of mathematical modelling, we strive to gain an understanding of analytic and algebraic structures behind the phenomena occurring in nature, social, or engineering problems. Based on these fundamentals, we are conducting and providing research and education in developing, validating and relating such models to reality.

Differential Equation Group

■ Professor: Takayuki Kobayashi ■ Associate Professor: Satoshi Masaki ■ Assistant Professor: Hajime Koba (concurrent)

Differential Equation Group's Website

We research and provide education in the field related to mathematical structure of nonlinear partial differential equations, which often appear in the studies of fluid mechanics or nonlinear fiber optics. In connection with this, we are developing an analytical method using the topological computation based on functional analysis, stochastic differential equation, and infinite-dimensional mechanical systems.

Applied Analysis Group

■ Professor: Michinori Ishiwata ■ Lecturer: Takahiro Okabe ■ Assistant Professor: Hajime Koba (concurrent)

Applied Analysis Group's Website

By means of mathematical analysis composed of numerical methods, nonlinear partial differential equation, nonlinear functional analysis, we elucidate the mathematical structure of problems in fields of natural science, engineering, medical science, and provide education and research on topics concerning many-body problem, biological functions, condensations, algorithms for numerical methods, and so on.

Area of Statistical Science

In this area, we offer education and research related to the development of analytical methods and applications of data-based modelling, concerning the analysis of phenomena that have a complex correlation and a strongly nonlinear structure along with errors and fluctuations, such as biological phenomena or social phenomena.

Statistical Analysis Group

■ Professor: Joe Suzuki ■ Associate Professor: Fuyuhiko Tanaka ■ Assistant Professor: Yuusuke Kaino (concurrent)

Statistical Analysis Group's Website

We consider the study and application of fields of computational statistics including machine learning, information theory, and Bayesian statistics. Usually, we propose a learning algorithm, implement it by a software, apply it to a real data set, and then evaluate its accuracy and computation time, though, whenever possible, we also try to make an understanding of its meaning by knowledge of information geometry, or to think of whether we got a reasonable estimate result compared to the number of samples (i.e., model selection). As an example of applications of the field, one of our accomplishments includes a learning algorithm based on undirected forest or Bayesian network that is used to analyze the probabilistic relationship among multiple variables, such as that of genomic analysis or stock price analysis. Apart from that, we are also interested in the topic related to statistical inference of quantum system.

Data Science Research Group

■ Professor: Yutaka Kano ■ Lecturer: Yoshikazu Terada ■ Assistant Professor: Yuusuke Kaino (concurrent)

Data Science Research Group's Website

An important purpose of multivariate analysis is to identify any relations among many variables based on statistical data. The recent topics in this field are new modeling and statistical causal inference. In this research group, we apply mathematics and computers extensively to study structural equation modeling, graphical modeling, and independent component analysis as well as survival analysis in biostatistics. Our research includes methodological and application aspects.

"Stand-alone Data Scientist Training Program"

■ Specially-Appointed Professor: Etsuo Hamada ■ Specially-Appointed Assistant Professor: Mariko Takagishi ■ Specially-Appointed Researcher: Kazumi Horie