There are many complex social systems, such as finance, security, the environment, distribution, and medical care; these systems continue to grow larger and more diverse. To analyze such complex systems, mathematical modeling and big data analysis need to play a greater role alongside conventional science and technology. Due to the diversification and growing sophistication of data analysis techniques in recent years, integrated training in scientific methodology and real science, such as mathematical science and data science, is essential. Mathematical modeling is the branch of mathematical science that employs mathematical methods to produce a model to help solve problems and elucidate complex phenomena. Solving problems facing modern society is the essential basis of contemporary science and technology. Meanwhile, data science is a scientific methodology that gathers, analyzes, and makes use of large-scale and mass data (big data) for research, technology, and service development. The new research methods developed in the practice of data science draw attention and contribute to the development of innovative new industries and services and to the promotion of growth across all sectors of the economy.
To deal with current diversified and advanced data analysis, there is an increasing need for mathematicians and data scientists who can create and interpret large-scale complex simulations and emerging technologies in diverse fields such as medicine, information technology, and economics. The rapid internationalization of business has led to a shortage of mathematical and data scientists; therefore, the creation of a systematic mathematics and data science education program to produce experts in these fields is of the utmost urgency.
At Osaka University, we reorganized CSFI and established MMDS. MMDS aims to strengthen education and research functions and to produce the next generation of global mathematicians and data scientists through the development of a pioneering education program that systematically trains students in financial and insurance actuarial science, mathematical modeling, and data science.
MMDS combines the following three areas connected by a shared focus on complex systems: (i) the DFI focuses on complex financial economic systems; (ii) the DMM uses mathematical modeling to formulate and solve problems within complex systems; and (iii) the DDS analyzes large-scale and mass data (big data) accumulated from complex systems and utilizes these data for research, technology, and service development.
MMDS aims to contribute to society through continuous training of mathematicians and data scientists with the following set of educational objectives:
・To produce the next generation of financial and insurance industry leaders through the utilization of financial and insurance actuarial science.
・To produce mathematicians and data scientists with the knowledge and abilities to communicate with field researchers so as to develop and undertake integrated interdisciplinary research.
・ To produce graduates with the international competitive abilities to practice technological innovation using mathematics and data science.