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.

The purpose of the course is to introduce fundamentals on road traffic flow science and traffic engineering including traffic flow fundamentals, queuing theory, highway capacity and geometric design/network design, intersection control, Intelligent Transport Systems and its applications.

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.

広く産学官にわたってグローバルに活躍するために必要な「俯瞰力」を養成することを目指す。物質科学の各分野について最先端の知識を修得し、自分の専門分野と周辺分野がどのように関連するか、あるいはし得るか、について深く考察するために、第一線で活躍する講師の方々にその分野の最前線を概観していただく。さらに、それらの講義を通して異分野間のコミュニケーションを円滑に進めるための具体的方法論を学ぶ。 This survey course is designed to enable students to develop the broad perspective that is required of global leaders working in and across industry, academia, and government. Students will gain knowledge and insight on advancements in each field of materials science research, given by leading researchers working on the frontline in those fields. This will allow students to consider how peripheral fields are related to their own area of expertise, and to consider the potential for forging bridges between related fields in the future. In addition, students will learn specific methodologies designed to facilitate smooth communication among different disciplines.

The goal of this course is to strengthen students’ ability to apply insights from the behavioral sciences to the design of policies and interventions that enhance the well-being of individuals and societies across diverse global contexts. We will pursue this goal by: - Introducing key origins and recent advances in behavioral science research, drawing from psychology and behavioral economics. - Critically examining the gaps that persist between research, evidence, and real-world practice. - Applying core behavioral science theories and strategies to the analysis and design of policies and interventions, with specific policy domains or institutional contexts. The applications we explore will span multiple domains, including public health, the environment, management, education, business, politics, and international development. This class is not a comprehensive survey of behavioral economics or social psychology. Instead, it offers a curated selection of research and theories that are especially valuable for thinking about practical application.

This course will deal with wide range of issues from local to global levels faced at the interface areas between science, technology and public policy from comparative perspective of Japan, the US and Europe. It offers key theoretical issues surrounding Science and Technology and provides students with the tools and frameworks, such as risk assessment/ management and transition management, to analyze them. This course invites students from both natural science backgrounds (i.e. the graduate school of engineering, new frontier science and so on) and social science backgrounds (graduate school of public policy, law and politics, and economics and public policy). We expect students to acquire interdisciplinary perspective in addition to their primary major, which is one of the critical skill in analyzing complex social technical issues posed by science and technology.

The development and diffusion of science innovative technologies is indispensable for modern society. However, despite its benefits, the development of science and technology is not without various risks and social problems. So far as we are going to make societal decisions for the use of science and technologies with diverse social implications that encompass both risks and benefits, sometimes involving values implications, there is a need for mechanisms of decision making and management of the development and utilization of science and technology. Decisions can be different depending on environmental, institutional and cultural conditions. In addition, innovative policy instruments/ mechanisms to deal with rapidly changing science and technology, including regulatory measures, are required for implementing decisions. This course will deal with wide range of issues from local to global levels faced at the interface areas between science, technology and public policy from comparative perspective of Japan, the US and Europe. It offers key theoretical issues surrounding Science and Technology and provides students with the tools and frameworks, such as risk assessment/ management and transition management, to analyze them. This course invites students from both natural science backgrounds (i.e. the graduate school of engineering, new frontier science and so on) and social science backgrounds (graduate school of public policy, law and politics, and economics and public policy). We expect students to acquire interdisciplinary perspective in addition to their primary major, which is one of the critical skill in analyzing complex social technical issues posed by science and technology.

The course will take an intersectional approach to why we commonly find an underrepresentation of women in the Science, Technology, Engineering and Mathematics (STEM) fields. The course will begin by addressing our own unconscious biases and stereotypes and question the research behind male and female differences. We will cover the brief history of the underrepresentation of minorities and explore research articles on why and how women and other minorities have been excluded from STEM fields. We will primarily discuss how representation and the sense of belonging are important for diversity in the sciences to flourish. Students will be expected to read scientific articles, discuss them in class, and apply those concepts to examine their own social environments.

The course will take an intersectional approach to why we commonly find an underrepresentation of women in the Science, Technology, Engineering and Mathematics (STEM) fields. The course will begin by addressing our own unconscious biases and stereotypes and question the research behind male and female differences. We will cover the brief history of the underrepresentation of minorities and explore research articles on why and how women and other minorities have been excluded from STEM fields. We will primarily discuss how representation and the sense of belonging are important for diversity in the sciences to flourish. Students will be expected to read scientific articles, discuss them in class, and apply those concepts to examine their own social environments.

The course will take an intersectional approach to why we commonly find an underrepresentation of women in the Science, Technology, Engineering and Mathematics (STEM) fields. The course will begin by addressing our own unconscious biases and stereotypes, and question the research behind male and female differences. We will cover the brief history of the underrepresentation of minorities and explore research articles on why and how women and other minorities have been excluded from STEM fields. Students will be expected to read scientific articles, discuss them, and apply those concepts to examine their own social environments.