This is an introductory course on mathematical methods for public policy analysis, designed for GraSPP students without a strong background in mathematics. Students from non-economics, non-engineering, or non-science majors are especially welcomed. The course helps students develop a solid mathematical foundation, enabling them to apply essential mathematical techniques to public policy issues. It is structured into four parts: 1. differential calculus, 2. linear algebra, 3. multivariate calculus and constrained static optimization, 4. dynamic optimization and linear dynamic systems.

The objective of this course is to brush up the mathematical skills required in advanced mechanical engineering through solving the example problems. Besides, solutions of partial differential equations are explained with the emphasis of the related physics. The methods using Green’s functions for nonhomogeneous differential equations are explained. Singular perturbation problems and renormalization technique are also explained as tools to obtain the approximate solutions. Furthermore, homogenization method, optimal design, structural optimization and sensitivity analysis are explained.

This course aims to raise awareness on the critical role of space technology in our daily lives and the important implications it has on domestic policymaking and international relations. The first part of the course, titled “Space and Society”, provides an overview of major space technologies and their applications. It then demonstrates how space assets have become a critical infrastructure on which advanced societies are over-reliant, and the hazards and threats that they are facing. The second part of course delves into political science and international relations. It addresses the various approaches to space policymaking, the structure of international relations in outer space and the major challenges ahead for the space sector. This course will be a part of the global effort to map threats and consequences for space sustainability conducted by the United Nations Institute of Disarmament Research.

現代の科学技術の諸分野において，扱う現象を数式を用いて表し（数理モデル化），得られた数理モデルの解を解析するというアプローチは必須のものとなっている．ところが，数理モデルの解（厳密解）を陽に書き下すことは不可能なことが多く，コンピュータを用いた数値計算で近似解を得るのが有力な選択肢となる．本講義では，数値計算を行う対象として最も基礎的な問題（連立一次方程式・非線形方程式・関数の補間・積分・常微分方程式）を取り上げ，数値解析の手法や考え方を紹介する． 数値解析の立場では，特に(1)「アルゴリズム導出のアイデア」，(2)「アルゴリズムの数学的正当化」の2点が重要である．上に挙げた基礎的な問題ですら，厳密に解を求める手軽な公式がない・公式があっても数値計算には現実的ではないといった状況に直面するため，元の問題に対して「近似」や「離散化」といった操作を施し，コンピュータで計算可能な公式（アルゴリズム）を得る．このとき，最終的なアルゴリズムに到達するための近似や離散化のアイデアを理解するのが(1)の段階である．さらに，（一般に同値変形でない）近似や離散化の操作を行っても本当に問題ないのかということをきちんと考察するのが(2)の段階である．いずれのステップにおいても，数学的議論が理論の土台として重要な役割を果たしていることを解説する． 講義で学んだアルゴリズムをプログラムとして実装し，実際に数値計算を行ってその有効性を確かめる実習を行うことが望ましいが，そのために計算数理演習の履修もすすめる．なお，進度に応じて講義内容を変更する場合がある．

Statistics and biometrics have emerged as crucial disciplines not only in agricultural sciences but also in various other fields. This significance is primarily attributed to three factors: Firstly, advancements in data measurement techniques have facilitated the collection of extensive and diverse biological and agronomic data that were previously unattainable. Secondly, the evolution of data science methodologies has enabled the integration and modeling of such collected data. Thirdly, the enhancement of computational capabilities has empowered the utilization of these methodologies. These advancements have rendered statistical and biometric methods indispensable for extracting insights from the vast and varied biological and agronomic datasets. Throughout this lecture series, a diverse array of biological and agronomic datasets will serve as illustrative examples to demonstrate various analytical methods. Delivered in a hands-on format, utilizing R, Python, and Matlab, the aim is to equip students with practical analysis skills. The initial portion of the course, spanning the first one-third, will focus primarily on techniques for summarizing, visualizing, and modeling relationships within multivariate datasets. In the subsequent one-third, students will delve into linear models, linear mixed models, local regression, and nonlinear models. Finally, in the last segment, students will explore image analysis, machine learning, and deep learning methods. While the course will cover a broad spectrum of methods, ranging from introductory to advanced levels, the emphasis will be on developing the capability to independently conduct analyses rather than on elaborating on the theoretical underpinnings of the methods.

Course Objectives. The purpose of this class is for those who have not studied economics to acquire basic knowledge of microeconomics. Overview. This course covers the introductory microeconomics to students who are not majoring in Economics. It provides key concepts, economic ideas, and a framework for learning about microeconomics. The course places primary emphasis on the role of market, and then analyzes the role of government in the market.

This course aims to raise awareness on the critical role of space technology in our daily lives and the important implications it has on domestic policymaking and international relations. The first part of the course, titled “Space and Society”, provides an overview of major space technologies and their applications. It then demonstrates how space assets have become a critical infrastructure on which advanced societies are over-reliant, and the hazards and threats that they are facing. The second part of course delves into political science and international relations. It addresses the various approaches to space policymaking, the structure of international relations in outer space and the major challenges ahead for the space sector. This course will be a part of the global effort to map threats and consequences for space sustainability conducted by the United Nations Institute of Disarmament Research.

This course aims to cultivate internationally competitive young researchers equipped with literacy and competency to become future leaders in industry and academia. The course deals with multidisciplinary application skills and the in-depth research in specialized fields so that students accomplish the ability to work in a broader spectrum and apply one’s skills to a multidisciplinary setting. The topics of the course include medical and biomedical robotics, medical high-tech industries, disease prevention, health care system, science technology and industrial policy, energy technology, and health security and community resilience.

This course aims to provide first-time learners of economics with solid foundations for understanding introductory macroeconomics. To this end, students will learn basic concepts in macroeconomics, such as GDP, unemployment, inflation, exchange rates and, based on them, how to use workhorse macroeconomic models to analyze consequences of a variety of economic shocks and policy interventions. By taking this course, students are expected to have a deeper understanding of how the macroeconomy functions and be able to critically assess economic news and conventional policy measures.

This course aims to understand current streams on international intervention. Against internationally recognized non-intervention principle, international intervention has been practiced for years. We mainly read journal articles on international intervention which include those on related topics such as responsibility to protect and humanitarian intervention, and case studies in several regions.