The method of big data, which involves collecting and analyzing large volumes of data to discover new insights and knowledge previously unknown, is widely used to improve society, organizations, and operations. Additionally, IoT (Internet of Things) and CPS are gaining attention as information systems that facilitate big data analysis. This lecture will provide an overview of big data, IoT, and CPS, as well as the information systems that support them, and explain the issues involved in utilizing big data. Toshiyuki Amagasa   Center for Computational Sciences / Center for Artificial Intelligence Research, University of Tsukuba

In this lecture, we will address the challenges of black box models in machine learning in relation to trustworthiness, fairness and utility of AI application. We will examine the mechanics of specific models, showing, what makes some models interpretable, and how they become obscure. The session will also cover common technical solutions to mitigate black box issues and present illustrative use cases for these techniques, along with an overview of the current challenges in the field. Bogdanova Anna   Institute of Systems and Information Engineering, University of Tsukuba

Digital Nature group at University of Tsukuba conducts research in the fields of HCI, CG, CGH, and haptics, investigating the communication means beyond the displays, and creating technologies for the modern day computer-centric society by fusing such areas as VR, AI, and digital fabrication. By modeling human properties and defining them as information communication problems through numerical analysis and simulation, we aim for an ecosystem in which humans and computers coexist. For this purpose, we are working on the idea of digital nature, which includes research on using interaction with light and sound in space, lasers, high-power ultrasound, magnetic fields, human behavior control, and more. Yoichi Ochiai   University of Tsukuba,Library, Media, Media Creation

Data science can be applied to each of the three fields of medicine: basic, clinical, and social. In basic medicine research, data science is used for many applications, such as genomic analysis. In clinical medicine, which is about caring for the medical needs of patients, data science is also employed, such as in the use of AI in image diagnosis. In this lecture, I will focus on social medicine, especially on Health Service Research (HSR). In order to realize high-quality health services, we need to take a longitudinal point of view – examining health behavior in daily life, access to clinics and hospitals, and medical treatment. Further, we need to investigate how health services are operating at the community level, including long-term care and, at the same time, it is necessary to a broad perspective of how each medical or long-term care services is provided. To get such a big perspective, we need access to big data. In this lecture, I will also touch on epidemiology and statistics, which are the foundation of social medicine, and explain the way of thinking for approaching data science. I will also address the current state of big data on medical and long-term care in Japan. Nanako Tamiya   Faculty of Medicine, Health Service Research Department

This lecture explains how and why data science have been essential to life science research. Haruka Ozaki   Faculty of Medicine

This course introduces the aerodynamics and flying characteristics on modern soccer balls using a wind tunnel and kick robot to students taking this course. Sungchan Hong   Faculty of Health and Sport Sciences

An interdisciplinary field of “Digital Humanities” connecting humanities and information science will be discussed in terms of its mission and relation to data science, with some practical examples introduced. Waki Toshihito   Faculty of Humanities and Social Sciences

This lecture introduces the Ethical, Legal, and Social Issues (ELSI) regarding the artificial intelligence. The ELSI of AI tackle the problem of human right violation caused by AI in the human society, whereas the most studies on AI focus on the problem of how analyzing and utilizing data. In the lecture, I will explain some ELSI discussed in the guidelines about ELSI of AI. Kazuto Fukuchi   Faculty of Engineering, Information and Systems

In recent years, efforts to create a data-driven society based on the Society 5.0, in which all people and things are connected by IOT and new values are being created, are taking place in many different fields. In this lecture, we will discuss tsunami height prediction as a familiar topic. Through this topic, we hope you will learn how the integration of data science with advanced instrumentation and large-scale simulations will make it possible to realize a data-driven society. Yasuhiko Igarashi    Faculty of Engineering, Information and Systems

This lecture introduces researches related to football, and gives an overview of the data collection and analysis methods used in each research, such as "game analysis", "GPS data", "EEG" and "eye movements". Masao Nakayama   Faculty of Health and Sport Sciences

In this lecture, I will show several example of recent studies that illustrate the usefullness of the data science in social sciences. To be accessible for those who major in other subject, I will use a lot of graphs and video. Hisahiro Naito   Faculty of Humanities and Social Sciences

The artificial radioactivity data in the ocean, air, and soil were collected from around the world and a set of database was created. I estimated the total amount of 137Cs deposition in the Northern Hemisphere and distribution of 137Cs deposition by analyzing the collected data. The total amount of cesium-137 in the Northern Hemisphere was 765+-79 PBq and this was 40% higher than in previous reported 545 PBq by United Nations Scientific Committee on the Effects of Atomic Radiation. Spatial distribution of 137Cs deposition was also presented.
The ocean part of the constructed database was provided to the International Atomic Energy Agency's database of artificial radioactivity in the marine environment and contributed to the construction of a global scale database together with other sources. The Center for Research in Isotopes and Environmental Dynamics at the University of Tsukuba now manages a database site to publish environmental radioactivity data related to the Fukushima accident with a DOI, and also provide a search site to retrieve radioactivity data which already published outside of the site at Univ. of Tsukuba. Michio Aoyama   Faculty of Life and Environmental Sciences

Introduction to hypothesis testing by Ken-ichi Koike. Koike Ken-ichi   Faculty of Pure and Applied Sciences

In this lecture, we will discuss a collaborative project among the University of Tsukuba, Intel Corporation, and Tsukuba City Hall that established a social networking service (SNS) community (Facebook community: Tsukuba Civic Activities Cyber-Square) aiming to strengthen cooperation between a local government and civil society. The project faced a problem of periodically observing a decline in Facebook community activity, and we will introduce the data science research methods that were used to analyze and clarify the problem.
Shingo Nahatame   Faculty of Human Sciences

For those of you in the School of Arts and Design, data science may be a field that you are not familiar with, or would rather have avoided. The mere mention of computer-based analysis can make you distance yourself from it.
However, you live with a smartphone in your hand as much as a pencil, and you use a small computer every day. It should be a familiar tool, right? Therefore, in this lecture, I will explain the points of contact and the way of thinking about data science for you in the School of Arts and Design. Hiroyuki Yamada   Faculty of Art and Design

The Behavioral Design Laboratory at the University of Tsukuba conducts behavior design research using the latest behavioral imaging technology to describe, predict, and control human social interactions based on applied behavior analysis. In this lecture, I will give an explanation of how to clarify mental phenomena through scientific and objective data, showing studies in children with autism spectrum disorder, which is characterized by lack of social interaction. Soichiro Matsuda   Faculty of Human Sciences

Biodiversity, which makes our rich life possible, is facing the greatest crisis among all environmental problems. In this lecture, we will discuss the evolution and crisis of living organisms from plant specimens accumulated in museums since the 14th century and international databases. First, the most closely related plant to the model plant Arabidopsis thaliana, Arabidopsis lyrata, has shown adaptive evolution, with a markedly different lifespan in lowlands and highlands. Second, global warming has already had a widespread impact on the distribution of 2339 plant species in Japan. Biological specimens are the intellectual assets of humankind, telling us about the evolution and crisis of life.
Kenta Tanaka   Faculty of Life and Environmental Sciences

Disability science is a discipline that explores the nature of human beings themselves through concrete support for people with disabilities and the basic research that underpins this support.
I explain why disability science needs data and the nature of data that focuses on disability on the part of society. I will then explain the sensitive handling of data in relation to the term 'disability', and the visibility and invisibility of disability as an 'outlier'. Finally, I present a case study of 'data-based decision making' in a welfare institution, using data not only in the context of research but also in practice. Ginga Sasaki   Faculty of Human Sciences

In this lecture, we will discuss a collaborative project among the University of Tsukuba, Intel Corporation, and Tsukuba City Hall that established a social networking service (SNS) community (Facebook community: Tsukuba Civic Activities Cyber-Square) aiming to strengthen cooperation between a local government and civil society. The project faced a problem of periodically observing a decline in Facebook community activity, and we will introduce the data science research methods that were used to analyze and clarify the problem.
Muneo Kaigo   Faculty of Humanities and Social Sciences

This lecture introduces the application of machine learning for robots to manipulate objects in real-world environments. It is often assumed that robots can easily perform human-like tasks if they are controlled by AI, but this is quite difficult. The lecture explains the problems and solutions for utilising data through real-world applications, such as how data can be used to manipulate robots appropriately. Sho Sakaino   Faculty of Engineering, Information and Systems

This lecture will explain the role of data science in urban planning. The course targets issues and places closely related to daily life, such as visualisation of issues from population and land use, development of residential areas with good living environments, understanding the impact of COVID-19 from human flow data, and regeneration of housing estates in ageing estates, and analyses of the current situation through field research and interview surveys, organisation of issues in urban planning systems, etc., social verification through experiments, and urban development proposals will be introduced. Sayaka Fujii    Faculty of Engineering, Information and Systems

This lecture explains the role of data science in business. It will introduce real-life examples, such as an examination of data-based marketing methods at Tsukuba-san Edoya, a regional company and ryokan, and an AI-based sales support trial at Mito Shinkin Bank, a non-profit regional financial institution, to explain experimental evidence-based management and upgrading business management systems through innovations in management information systems. Yukihiko Okada    Faculty of Engineering, Information and Systems

Data visualization is the process of changing the representation of data to make it visible to people. By presenting a visual representation of data to people, it can help them understand, discover, and gain insight into the data. However, we often find bad visualizations that do not serve these purposes. In this talk, I will use bad examples to introduce the relationships between human visual characteristics, target data, and visual representation techniques, and explain the importance of being aware of these relationships. Kazuo Misue   Department of Computer Science, Institute of Systems and Information Engineering

In recent years, there have been very active attempts to incorporate data science methods into chemical research. This talk will explain how data science can be used in chemical research, giving specific examples. Daisuke Tanaka   Kwansei Gakuin University／School of Science／Department of Chemistry

This is an introductory lecture on artificial intelligence and machine learning. You will learn what artificial intelligence can do and how artificial intelligence is impacting our everyday lives. Machine learning plays an important role in the current development of artificial intelligence. This lecture also teaches you how machine learning actually works.
Yukino Baba   Graduate School of Arts and Sciences, The University of Tokyo