Creating Society, Connecting to the Future.

School of Information and Data Sciences,
Nagasaki University
国立大学法人The Mission of the School of Information andData Sciences
Professor Ryuei NISHII, D.Sc.

Director, Oﬃce for Establishment of an Information-related School

What is the diﬀerence between information and data?
For example, how many points can Japan score
against Brazil when they play each other in the soccer
World Cup? You can get a vast amount of data fromthe Internet, including not only the results of previous
matches between the two countries and FIFA rankings but also the results of recent matches with othercountries and the condition of key players. You canthus predict scores by extracting information usefulfor predictions from this big data.
In general, raw observations of phenomena can be called data. Data selected andcondensed to meet a speciﬁc purpose is called information. Rational decision-making based on the information and data (evidence) is an essential skill for individuals
and companies in this modern age of big data. The School of Information and Data
Sciences oﬀers students a series of know-how, from information extraction to decision-making, based on mathematical models such as AI, machine learning, mathematics, and statistics. Furthermore, we return the results to society as “products”
by using information technology. This foundational training is not focused on a speciﬁc ﬁeld. It teaches students versatile methods that can be applied to all academic
ﬁelds and companies that handle information and data.
Japan is seeking build “a human-centered society” as the next stage of an advanced information society. The School of Information and Data Sciences will contribute to building society with students who wish to study information and data
as a scientiﬁc discipline, students who seek to actively involve themselves in hot
topics in a wide range of ﬁelds, and students who wish to improve themselves.

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Features of the School of Information
and Data Sciences
Curriculum that can be tailored to each student’s envisioned future●After learning the foundations during their ﬁrst year, students choose either the Data Science
Program or Information Science Program.
●Regardless of the program they select, students can choose courses they are interested inand learn a wide variety of ﬁelds.

Utilization of big data in healthcare and tourism●Students will carry out statistical machine learning-based data analysis to support healthcare
by using data accumulated in the medical and healthcare ﬁelds, where Nagasaki University isa leader.
●Many tourists visit Nagasaki. Students will conduct statistics-based big data analysis, which
extracts features from tourists’ behavioral data. Students will thus help expand municipalities
and industries.

“Real-World Solutions Project”‒ engaging students in solving challenges faced by society and companies●Students will tackle practical problems while in school by working with municipalities and local
companies to develop problem-solving and communication skills.
●Each student will have opportunities to gain problem-solving experience, such as vitalizationof local companies, eliminating community problems, etc.

Nurturing Human Resources
The School of Information and Data Sciences fosters human resources
who contribute to society as core human resources in a variety of ﬁelds.
The nucleus of the School of Information and Data Sciences is Nagasaki University’s Computerand Information Science Program in the School of Engineering. The School of Information andData Sciences adds data science education and research functions. We welcome diverse
students who are interested in not only the subjects of information science and data science
themselves but also in a variety of academic disciplines to which they can be applied. In thisexciting environment, we train human resources such as “information scientists” skilled in using
AI for IT business and “data scientists” skilled in big data analysis, medical information analysis,
and other types of data analysis.

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Composition of Curriculum
1st Year
Students gain

Common courses

Foundational mathematics / Computer science /Communication /Programming (C,Python)foundation of advanced,

Students select desired courses
from 2nd Year

specialized knowledge.

Information Science Program

Data Science Program

Specialized Tracks
IoT courses

AI courses

2nd to 4thYear
Students take courses
to gain specialized
knowledge andSE courses

improve applied skills.

Information
technology-related

Statistics-related

Medicine/
healthcare courses

Society/
tourism information courses

Information security courses

Students acquire and deepen
specialized knowledge with elective courses

Graduation research

Career Options after Graduation

Graduates of the School of Information and Data Sciences will be active in a wide range
of ﬁelds and contribute to creating the society of the future.

Wide range of next steps

Development ofintelligent robots

Development ofsystems

Management,
municipalities

Tourism

Healthcare

Technologies for building
partners of the future

Create new systems forsupporting society

Create new businesswith big data

Create new ﬂow of people
by analyzing tourism data

Save lives with data

Explore specialized domains
and advance further

Enter the Graduate School of Information
and Data Sciences (planned)

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“Real-World Solutions Project”
The School of Information and Data Sciences has established a course called “Real-World
Solutions Project.” For four years from their ﬁrst year to their fourth year, students work incollaboration with municipalities and local companies to discover and address challenges
facing actual society. The project also seeks to foster universally needed skills such as creativity, communication ability, and critical thinking as participants explore approaches to solutions. Through the project, the School of Information and Data Sciences seeks to develop
human resources who can actively work in an information society. Furthermore, students candeepen their studies in school by applying the specialized skills and techniques they learnedin classes and practicums to practical problems in actual society in a feedback cycle.

Post-Graduation Options
Graduates of the School of Information and Data Sciences can advanceto the Graduate School of Information and Data Sciences (establishment
planned) or expect to ﬁnd employment in the following industries:

Information Science Program
System engineering (SE)-related
Companies creating new services with robots and IoT
Companies related to promotion of information industry
Information security industry, information system development industry

Software Development

IoT-related
Robot Process Automation (RPA) application industry, aerospaceindustry, civil engineering/construction industry, marine industry
AI robot development

Development of embedded devices

Data Science Program
Society and tourism information-related
Data-based tourism policy-making, regional revitalization policy-making,
Shinkansen tourism policy-making
Tourism policy by data

Medical and healthcare information-related
Diagnostic outsourcing, new drug creation ventures, remote diagnostic
services, health tourism industry
Pathological diagnosis
by AI

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Drug discovery by genome analysis

Information Science Program
Beginning with foundational knowledge in information science,
students will gain problem-solving skills and communication skills
through practical courses.
IoT coursework model■IoT-related■Information
technology-related■Information
security-related・Software engineering

・Programming exercises

・Information mathematics

・Embedded systems

・Information engineeringexperiments

・Cryptographic theory

・Control engineering

Skills tobe acquired

・Pattern recognition

・Network security

Students will acquire knowledge of the IoT ﬁeld and data analysis
abilities. With these knowledge and skills, students can be expected
to contribute to the development of robots and AI-equipped devices.

SE coursework model■SE-related■Information
technology-related■Information
security-related・Software engineering

・Programming exercises

・Information mathematics

・Database・Information engineeringexperiments

・Cryptographic theory

・Computer architecture

Skills tobe acquired

・Pattern recognition

・Network security

Students will acquire data analysis skills and information security
skills. With these abilities, students can be expected to become
active as system engineers equipped with high expertise demanded
by society today.

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Research Themes（Information Science Program）
Scientiﬁc Knowledge and Data-Integrated Research
Because we have scientiﬁc knowledge cultivated to this day, should AI just learn data? We areengaged in research that integrates existing scientiﬁc methods, which explain the composition ofdata with mathematical models expressing humanknowledge, and the new methods of data science, as
represented by deep learning. For example, a doctor
must be able to explain the results of a data analysis
that support the diagnosis. In such a case, data sciencegrounded in human knowledge will be beneﬁcial.

Next-Generation Computing
Underpinning the dramatic development of information technology in modern society is the
sharp rise in the performance of computers themselves. However, going forward the conventional approach of simply extending computers’ performanceas in the past will be difﬁcult. We are conducting researchon realizing “soft” computers in which logical ﬂexibility is
introduced into their hardware structure. At the sametime, we are also actually creating these computers.

Audio Signal Processing
Audio user interfaces like speech recognition are technologies that anyone can easily use. We
are conducting integrated research on speech and language with the goal of creating man-machine interfaces using speech recognition and comprehension anddialogue systems. We are also conducting research on bioacoustic
signal processing to identify, for example, healthy patients and patients with pulmonary illnesses using respiratory sounds obtained by
auscultation and to infer information about an infant’ s condition
using his or her crying sounds.

Image Processing and VR/AR/MR
As information devices become more advanced and improve in performance, technologies suchas VR (Virtual Reality), AR (Augmented Reality), and MR (Mixed Reality) have become commonplace. These technologies can be used easily by anyone. We are conducting research on applied technologies using VR/AR/MR to support domains like rehabilitation medicine and tourism. In addition,
due to the expansion of the Internet, the illegal distribution of images
and video over networks has become an issue. We are researching
digital watermarking as a solution to this problem.

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Data Science Program
In this program, students are trained to become data scientists
who can analyze big data and contribute to the development ofsociety.
Medical/healthcare information coursework model■Statistics-related■Medical/healthcare-related■AI-related・Descriptive andexploratory statistics

・Medical/healthcare informatics

・Big data analysis

・Information statistics

・Bioinformatics

・Data analysis exercises

・Healthcare

Skills tobe acquired・Statistical machine learning
・AI

Students will acquire healthcare data analysis skills and the ability
to connect their knowledge to healthcare research and policy.

Society and tourism coursework model■Statistics-related■Society and tourism
information-related■AI-related・Descriptive andexploratory statistics

・Society and tourism
informatics

・Big data analysis

・Information statistics

・Social policy/Behavioral
science・Data analysis exercises

Skills tobe acquired・Statistical machine learning
・AI・Application of VR/AR

Students will acquire skills including Mathematical/Statistical data
analysis techniques, composition and development of data analytic
systems (programs), and methods of applying data analysis(management strategies, policy proposals, etc.).

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Research Themes（Data Science Program）
Large-scale Genomic Data-based Predictive Modeling
We are developing mathematical models and algorithms forsearching for genes relevant to predicting diseases from genomic data. First, strongly relevant genes are narrowed
down from genomic data (1). Using the discovered genes(2), predictive modeling is performed (3). The developmentof algorithms makes use of extensive knowledge of mathematic statistics, biostatistics, genetics, and machine learning.

①関連遺伝子の絞り込み②関連の強い遺伝子③予測モデリング

Overview of Nagasaki Prefecture Tourism Vitalization Support System
The ﬁgure below shows an information platform developedin cooperation with Nagasaki Prefecture and Nagasaki City
for collecting and analyzing tourism-related big data. Thissystem provides information for quick visualization, such aswhere tourists are staying and how long they stay in spots,in order to understand tourism trends. The information isbased on smartphone log information and information available on the Web.

AI Mathematical Modeling
The term AI (artiﬁcial intelligence) was coined about 60 years ago. At present, its leading technology is mathematical models called neural networks (NNs). NNs model human brain functions.
For example, when an image of a dog is entered as
input, an NN program outputs, “This is an image of adog.” The (third) AI boom that began around 2000 may
have ﬁnally subsided, but the technologies developed so
far continue to be critical.

Unraveling the Mysteries of Antiquity with Information and Data Sciences
We are tackling the mystery of Egyptian pyramids, built
about 4,500 years ago. We know almost nothing about these
giant buildings constructed by humankind. How were thestones assembled? What were inside the pyramids? And,
how were they designed? For ancient Egyptians, the designand construction of pyramids solved an unknown problem.
Unraveling this mystery by humanity today will offer important clues for solving our own yet-unknown problems.

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Digitization in the pyramid（Photo by Yukinori KAWAE）

Giza Pyramid Survey

Messages fro m Facu lty Members
Let’s See How Computers Think
Computers are just computers, as the name suggests. The key to solving problems with information technology is, therefore, to translate them into
computational problems. It looks difﬁcult, but it's not. AI, or the computation of pattern recognition and machine learning, is actually composed mostly of repetitions of simple arithmetic operations. Let’s learn
not only computer skills but also the expertise to provide IT solutions
by understanding their underlying mechanisms to the fullest extent.

Associate Professor Tomoya SAKAI

Areas of Research:
High-dimensional data science and its applications

The Allure of Data Science
I became interested in the world of data science
Areas of Research:when I felt, “Data analysis is actually useful!” after
Post-model-selection statistical inference
taking a class in mathematical statistics offered by
the math department. I then joined a mathematical statistics lab, and havecarrying out research in this ﬁeld ever since. In 2012, Harvard Business
Review said that being a data scientist was “the sexiest job” of the 21st
century. Without data scientists, modern society would not be possible.
Are you interested in experiencing the world of fascinating data science?

Associate Professor Yuta UMEZU

Data-based Decision Making
In an era that requires efﬁcient allocation and disAreas of Research:tribution of limited tourism resources, budget, andTourism policy, data mining, crowd sensing
personnel, understanding the current condition accurately is critical. How can we accomplish this, and how can weachieve better results from the current condition? Data science grapples with these challenges. Won’t you experience data science andtransform society?
Associate Professor Yu ICHIFUJI

To Future Information and Data Scientists

The ﬁrst science, 400 years ago, was created inlarge part by Galileo. It began with correct observations of phenomena. Eventually, mathematicalmethods advanced, and unknown phenomena could be predicted bytheory. In the late 20th century, computer science was born. This gave
rise today to the science of “information,” which ﬂows throughnetwork̶that is, digital data. In other words, information and data sciences were born. Learn these new sciences, and one day you will
create a new science. We are waiting for the next Galileo.

Professor Ichiroh KANAYA

Areas of Research:
Design studies, cultural asset science/museum studies,cultural anthropology/folklore studies

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Data Science for Health and Medicine

Professor Masao UEKI

Areas of Research:
Mathematic statistics,
statistical genetics, biostatistics

We are advancing efforts to make healthcare big data useful for elucidating disease mechanisms, and furthermore, for the prevention andearly diagnosis before onset. Statistics has traditionally played an important role in medicine. Going forward, we will develop statistics asmedical data science that incorporates advanced technologies like machine learning and AI to handle complex big data. Health and medicine
contains intimate challenges directly related to life. Tackling them is extremely rewarding, with the possibility of making great contributions to progress in thisﬁeld, and furthermore, to our future. Won’t you take on this challenge with us?

Associate Professor Norio SETOZAKI

Making Learning a Science

Areas of Research:
Educational technology, science education

We are exploring how to essentially confront “learning” while enjoying
oneself. As a tool to accomplish this, we have developed a learning
system that applies technologies like VR (Virtual Reality) and AR (Augmented Reality). Furthermore, we seek to clarify the challenges and effectiveness of our developed system and provide learning that is more
effective. Our methods include analyzing learners’ biological information
with analysis of speech and behavior during the learning process. Won’t you come anddevelop exciting and attractive “learning” together with us at the School of Information
and Data Sciences?

IoT/AI Integration

Professor Toru KOBAYASHI
Area of Research: Intelligent robots

IT (Information Technology) has the great potential to solve the world’ s
problems and bring happiness to people. Making this a reality requires
skills to understand people’s unseen needs and realize solutions. The Intelligent Robots Laboratory is advancing the research and developmentof new services useful to people. We do this by integrating AI and IoT(Internet of Things), which connects all things on a network. For example, we are researching SNS-mediated robots, which can communicate with the elderly who cannot
use smartphones by using SNS (social networking services); telemedicine robots, whichmake possible diagnosis and treatment of dementia in patients living on remote islands
with few doctors; and systems for automatically removing blue-green algae from lakes
and marshes by using a network of drones and unmanned boat-type robots. Throughthese research efforts, we can understand the unseen needs of people and develop advanced IoT and AI-related technologies to address them.

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Entrance examination information
Admission quota

110 students

Breakdown●General Entrance Examination :70students (late February exam),15students (mid-March exam)●Admission by Recommendation I : 5students, Admission by Recommendation II :10students●Foreign Exchange Students A (General Admission) : 5students,
B (Admission by Recommendation) : 5students,
C (International Baccalaureate) : a few students

To Sasebo →Access←To Nagasaki
Sta.

Peace Park

Urakami Sta.

OhashiUniversity Hospital
Urakami Sta.
（Bus stop and Tram）

Iwayabashi

206

Atomic Bomb Museum

Nagasaki University
Bunkyo campus

Wakaba-machi

Nagasaki University（Bus stop and Tram）

Chodai-higashimon-mae
Bus stop

Showa-machi Bus stop

Japan Railway

Get oﬀ at JR Urakami Station (Nagasaki Main Line). Then take a streetcar or bus.

● Streetcar from JR Urakami Station ●Get on streetcar (destination : Akasako) at “Urakamiekimae” stop →Get oﬀ at “Nagasaki University” stop (about 10 minutes)● Bus from JR Urakami Station ●Get on bus (destination : Nameshi/Togitsu) at “Urakamiekimae” stop →Get oﬀ at “Nagasakidaigakumae” stop (about 10 minutes)

Highway Bus

Highway bus (Nagasaki-bound via Urakami) → Get oﬀ at Showa-machi →Walk 15 minutes to Nagasaki University East Gate or 20 minutes to Main Gate.

From Nagasaki Airport

From Nagasaki Airport (Omura City), take Prefectural Bus “Nagasaki Airport Limousine”(destination : Nagasaki via Urakami) → Get oﬀ at Chodai-higashimon-mae(~50-minute ride) →Walk 3 minutes

国立大学法人NUrakami Tram Depot

School of Information and Data Sciences, Nagasaki University
HP https://www.idsci.nagasaki-u.ac.jp/
Nagasaki University Oﬃce for Establishment of an Information-related School
1-14 Bunkyo,Nagasaki City 852-8521