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.
|Graduate School Division||Division of Mathematical Science||Division of Mathematical Science for Social Systems|
|Course of Study & Name of|
|Mathematical Science Course,|
Department of Information and Computer sciences
|Intelligent Systems Science Course,
Department of Systems Science
|Area||Mathematical Modelling||Statistical Science||Mathematical and Statistical Finance||Theoretical Systems Science|
Modeling in Finance
and Decision Making
|Professor||Takayuki Kobayashi||Michinori Ishiwata||Joe Suzuki||Yutaka Kano||Masayuki Uchida||Jun Sekine||Masaaki Fukasawa||Toshimitsu Ushio||Masahiro Inuiguchi|
|Associate Professor||Satoshi Masaki||Fuyuhiko Tanaka||Specially-Appointed Professor: Etsuo Hamada||Hidehiro Kaise||Takashi Matsubara||Naoki Hayashi|
|Lecturer||Takahiro Okabe||Yoshikazu Terada||Kosuke Morikawa|
|Assistant Professor||Hajime Koba||Yuusuke Kaino(Concurrent Position in
Kano Lab. & Suzuki Lab.)
|Specially-Appointed Assistant Professor: Mariko Takagishi||Kohei Chiba||Kei Noba||Nobuaki Naganuma||Naomi Kuze||Hirosato Seki|
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.
■ 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.
■ 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.
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.
■ 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.
■ 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.
■ Specially-Appointed Professor: Etsuo Hamada ■ Specially-Appointed Assistant Professor: Mariko Takagishi ■ Specially-Appointed Researcher: Kazumi Horie