Policies
1. Diploma Policy
With the explosive development of artificial intelligence technologies, data science is radically changing the nature of academia, technology, business, and daily life. The characteristics of mathematics as a pillar of this field are its rigor, which provides an unchanging theoretical foundation, and its versatility, which allows it to respond flexibly to changing circumstances. Mathematics is expected to play an important role in pioneering the future of human society by maximizing these strengths and through active collaboration in various fields. In particular, mathematical modeling, which enables mathematical analysis by formulating various problems from the real world as mathematical models, occupies an important position as an objective verification methodology in a wide range of fields of modern society.
Education and research in the Graduate School of Mathematics, the Graduate School of Information Science and Electrical Engineering, and the Graduate School of Economics, which are the Cooperative Graduate Schools of this degree program, all share an essential commonality that is the use of mathematical models to analyze and deepen the understanding of natural and social phenomena. In the Doctoral course of this program, based on the excellent specialized education and research in each of the Cooperative Graduate Schools, we will foster outstanding mathematical modeling talents who can co-create across organizational and disciplinary boundaries, conduct research in their specialized fields at an advanced level, and lead innovations at an international level. In the Master course, as a preliminary step, we will foster talents who can contribute to leading innovation by conducting research in their specialized fields in collaboration with various organizations and research groups with diverse perspectives and disciplines through basic mathematical modeling.
This degree program selects students with excellent mathematical skills and motivation to co-create with researchers from other fields who mainly study mathematics, information science and electrical engineering, and economics. While advancing the knowledge of their foundational disciplines, they are expected to create innovation by developing the so-called “Mathematics Five Forces” (MFF): (1) “mathematical ability,” (2) “statistical ability,” (3) “modeling ability,” (4) “co-creation ability” and (5) “emergence ability.” To establish Kyushu University “Da Vinci Program,” a flexible and personalized research mentoring system combined with a multi-mentor system will be provided so that each student can select from a variety of cross-disciplinary themes according to his/her academic needs and interests, and pursue his/her study and research. The curriculum will be organized with “mathematical modeling” as the common denominator.
The curriculum of this degree program is based on the specialized courses offered by the Cooperative Graduate Schools. It includes courses that enable students to acquire advanced mathematical modeling skills and gain experience in co-creation with researchers from different fields based on these skills. “Research and Thesis Courses” and “Major Education Courses” will be offered corresponding to the specialized curriculum of the Cooperative Graduate Schools. In addition, for students studying information science and electrical engineering, and economics, there will be “Transition Courses” to develop common basic skills required in modern mathematics. On top of that, the following courses will be established as the core courses that will guarantee the excellence of this degree program.
1. “Foundational Courses” (Master’s course) to foster broad and advanced mathematical and statistical skills as the foundation for advanced and cutting-edge mathematical modeling techniques.
2. “Internship Courses” (Master’s and Doctoral courses) to foster (a) “modeling abilities” for applying mathematical modeling in practical situations, and (b) “co-creation abilities” for collaborative innovation which involves various fields.
3. “Presentation Courses” (Doctoral course) to foster the ability to explain research topics and research directions in an easy-to-understand way across organizational and disciplinary boundaries.
The requirements for graduation from the Master’s course are 30 credits or more as indicated below, and a Master’s thesis which is required to meet certain criteria for high quality, and the final examination.
1. Foundational Courses: 4 or more credits (including 4 credits from “Mathematics I – XX”).
2. Internship Courses: 4 or more credits.
3. Research and Thesis Courses: 10 credits.
4. Major Education Courses of the Cooperative Graduate Schools: 12 or more credits
(Major Education Courses of the graduate school related to the degree field*).
*To enable systematic and effective learning, students are required to select appropriate courses from those offered by the Cooperative Graduate Schools under the guidance of their primary supervisor.
(The following courses may also be included in the “Major Education Course of the Cooperative Graduate Schools” (12 credits).)
・Transition Courses (Only for students who have passed the entrance examination of the Graduate School of Information Science and Electrical Engineering and the Department of Economic Engineering in the Graduate School of Economics).
・Foundational courses that exceed 4 credits.
・Courses in other graduate schools (except for the Cooperative Graduate Schools), which their supervisor deems necessary.
The completion requirements for the doctoral course are 16 credits or more, a doctoral thesis, which will be subjected to a thorough review to ensure high quality, and the final examination.
1. Internship Courses: 6 credits or more (including 2 credits of “Advanced Mathematical Modeling”)
2. Presentation Course: 2 credits
3. Research and Thesis Courses: 8 credits
(Master’s Degree)
In addition to the academic foundations acquired through the major education courses offered in the Graduate School of Mathematics, the Graduate School of Information Science and Electrical Engineering, and the Graduate School of Economics, the Master’s degree is conferred to the students who
(a) have acquired “mathematical ability,” “statistical ability,” “modeling ability,” and “co-creation ability” necessary for co-creative activities, together with basic “emergence ability,” (b) have completed a Master’s thesis based on high-level research with a background in co-creation with collaborators from different fields or industries, and (c) have passed the screening process.
(Doctoral Degree)
The doctoral degree is conferred to those who (a) have strengthened the academic foundation for the field of the degree to be conferred, which was acquired in the Master’s course, (b) have acquired MFF, i.e., high level “mathematical ability,” “statistical ability,” “modeling ability,” and “co-creation ability” necessary for co-creative activities, together with high level “emergence ability” necessary for generating innovation through co-creation with different fields and industries, (c) have completed a doctoral dissertation based on outstanding research in their specialized field, and (b) have passed the screening process.
The name of the major field of study to be added to the degree shall be one of the following.
○Master’s course
Master of Mathematics, Master of Mathematics Administration, Master of Information Science, Master of Science, Master of Engineering, Master of Philosophy, Master of Economics
○Doctoral course
Doctor of Philosophy [Mathematics], Doctor of Functional Mathematics, Doctor of Information Science, Doctor of Science, Doctor of Engineering, Doctor of Philosophy, Doctor of Economics
*Reference standard: Science Council of Japan, “Reference Standard for Curriculum Development for Quality Assurance of University Education by Discipline: Mathematical Sciences,” 2013
(http://www.scj.go.jp/ja/info/kohyo/pdf/kohyo-22-h130918.pdf)
B. Acquiring Knowledge and Understanding (Knowledge and Understanding) (Master’s Course)
B-1. Acquiring the basic concepts and knowledge required in modern mathematics: “mathematical ability” and “statistical ability” [For students studying Information Science and Electrical Engineering, and Economics].
B-2. Acquiring the broad range of mathematical foundation knowledge required in mathematical modeling and understanding general methodologies and specific examples: “mathematical ability,” “statistical ability,” and basic “modeling ability.”
C. Applied Knowledge and Understanding (Master’s and Doctoral Courses)
C-1. Applied Knowledge and Understanding (Application and Analysis) – Practical “Modeling Ability”
Describing various cross-disciplinary problems using mathematical language by applying mathematical modeling techniques developed through deepdiscussions and knowledge sharing across research fields.
C-2. Creation of New Knowledge (Evaluation and Creation) – “Co-creation Ability”
C-2-1.(Creation of new knowledge) Creating new knowledge by conducting mathematical analysis for mathematical models emerged from cross-disciplinary problems.
C-2-2.(Co-creation of new knowledge) Explaining knowledge obtained through mathematical modeling to researchers from various fields in the form of a thesis or oral presentations and co-creating knowledge through collaborative discussions.
D. Using Knowledge and Understanding in Practical Situations (Practice) – “emergence ability” (Master’s and Doctoral Courses)
Developing research in their specialized field, and acquiring the ability to create innovation through collaborative research with partners from industry and different fields by using knowledge and methodologies of mathematical modeling.
2. Curriculum Policy
In this degree program, in addition to “Major Education Courses” in each of the Cooperative Graduate Schools for obtaining the academic foundation related to the field of the degree that each student aims to acquire, the following courses will be set in order to acquire broad and advanced knowledge and skills necessary to understand and use mathematical modeling, and to get co-creation abilities in practical situations.
1. Foundational Courses and Transition Courses 《Objectives of B》 for developing “mathematical ability,” “statistical ability,” and basic “modeling ability.” (Master’s Course)
1-1. Mathematics I – XX 《Objectives of B-2》: First courses for students to thoroughly acquire the fundamentals of “mathematical ability,” “statistical ability,” and “modeling ability.”
1-2.Topics in Mathematics I – X 《Objectives of B-2》: Courses that students study from the fundamentals to applications about related topics to acquire the knowledge necessary for mathematical modeling.
1-3. Transition to Modern Mathematics I – VI 《Objectives of B-1》 [For students studying Information Science and Electrical Engineering, and Economics]: Courses for students who have not taken mathematics at the Bachelor’s education level to acquire basic knowledge and concepts of modern mathematics depending on the achievement level of students to smoothly complete this degree program.
2. Internship Courses to foster practical “modeling ability,” “co-creation ability,” and “emergence ability” 《Objectives of C and D》
2-1. Basic Mathematical Modeling 《Objectives of C》 (Master’s Course): Students will learn the basics in laboratories of other fields depending on their interests and preferences while collaborating with other students and junior faculties. Also, students will contribute from the aspect of mathematical modeling and grapple with joint research, co-authored papers, and conference presentations.
2-2. International Internship, Interdisciplinary Internship, and Industrial Internship 《Objectives of C and D》 (Doctoral Course)
These internships are elective compulsory courses in the doctoral course, which aim to strengthen co-creation abilities. In the International Internship, students will conduct practical research and R&D (business) training at overseas universities and research institutions. In the Interdisciplinary Internship, students will stay at research centers in different fields for a long term and conduct joint research by contributing from a mathematical modeling perspective. In the Industrial Internship, students will participate in research at companies under the cooperation of industry and conduct practical training in R&D (business).
2-3. Advanced Mathematical Modeling 《Objectives of D》 (Doctoral Course)
Students will be sent to internal faculty members in other disciplines as “Reverse Mentors” and lead faculty members and other students from a mathematical modeling perspective. The goals are to improve their skills and to bring innovative mathematical modeling and analysis methods to other fields by giving students themselves the experience of contributing to research in other fields through mathematical modeling.
3. Presentation Courses to foster practical “modeling ability” and “co-creation ability”
Interim Progress Presentation《Objectives of C》 (Doctoral Course)
Students will prepare an interim report focusing on their achievements up to the second year of the doctoral course and give an oral presentation. Based on the background, process, and future strategy of the research, oral presentations on Mathematics Co-creation Practices such as Basic Mathematical Modeling or Internships, and submitted materials, the achievement level and research strategy culminating in a doctoral dissertation will be evaluated, and the eligibility for writing a doctoral dissertation will be assessed.
4. Lecture Courses to foster “emergence ability”
Master’s research and thesis and Doctoral research and thesis 《Objectives of D》 (Master’s and Doctoral Courses)
The corresponding seminar courses are supervised by the faculty of Cooperative Graduate Schools, in which the students’ basic academic disciplines are developed. By taking these courses, students will further deepen and strengthen their foundation in the core academic areas of mathematics, mathematical sciences, information sciences, science, engineering, and economics. Students will also be able to conduct more advanced and cross-disciplinary research utilizing the mathematical modeling techniques and MFF acquired by taking this degree program. In this way, students will conduct research in their own academic field, leading to writing a master’s thesis or doctoral dissertation.
(Master’s Course)
Based on the submitted master’s thesis and final examination (oral presentation), the MFF Screening Committee, established by the GPMI Implementation Committee with program members and others as members, will review the thesis.
(Doctoral Course)
Based on the submitted doctoral dissertation and the presentation in the final examination (defense), the doctoral dissertation will be reviewed by the MFF Screening Committee (doctoral degree), established by the GPMI Implementation Committee with program members and researchers of co-creation fields, etc. as members.
The achievement of academic goals is evaluated based on the following policy (Assessment Policy). The GPMI Implementation Committee will continuously review whether there is a need to improve the research guidance system, teaching methods, arrangement of lecture courses, etc. based on the assessment results.
《Assessment Policy》
The achievement of academic goals will be evaluated at the degree screening.
3. Admission Policy
The Master’s Course in this degree program seeks students with academic backgrounds in Mathematics, Information Science and Electrical Engineering, Economics, etc., who have a basic knowledge of mathematics at the Bachelor’s level, and who are motivated to acquire a broad range of knowledge in mathematics and to promote their research using mathematics. We particularly welcome students who are interested in exploring advanced mathematical theories and using mathematical modeling for applied research, as well as those who are willing to be challenged and gain new knowledge in different fields or society.
The term “basic knowledge of mathematics at the Bachelor’s level” refers to the basic academic foundation and academic abilities essential for studying various scientific fields, including “Calculus” or “Linear Algebra” as taught to science students. In general, the requirements for admission are that students have acquired “mathematical skills” and “statistical skills,” including an understanding of the concepts of modern mathematics, which are typically studied in the Department of Mathematics at the School of Science, etc. However, for students who do not have acquired these skills, transition courses will be imposed after admission.
The doctoral course in this degree program seeks students with academic backgrounds in Mathematics, Information Science and Electrical Engineering, Economics, etc., who have the academic ability and practical applied mathematical skills at the graduate level, and who are willing to acquire a broad range of mathematical knowledge and to promote their own research using mathematics. The program particularly welcomes students who have experience in exploring and constructing highly developed mathematical theories and in using mathematical modeling for practical applications, as well as those who are willing to take on advanced problems in different fields, and to acquire new knowledge.
To confirm basic academic ability and academic foundation, in principle, applicants are required to take an entrance examination at existing departments such as those in the Graduate School of Mathematics, the Graduate School of Information Science and Electrical Engineering, and the Graduate School of Economics, etc. Applicants who successfully pass the entrance examination at existing departments will be qualified to apply for this program. The selection will be based on a documentary review of the applicant’s statement of reasons for application, recommendation form, etc., and an oral examination.
The selection policies described above are the same for working adults and international students. International students’ Japanese or English language skills will be verified through an oral examination.