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
- Software engineering
- Embedded systems
- Control engineering
■Information technology-related
- Programming exercises
- Information engineering experiments
- Pattern recognition
■Information security-related
- Information mathematics
- Cryptographic theory
- 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
- Software engineering
- Database
- Computer architecture
■Information technology-related
- Programming exercises
- Information engineering experiments
- Pattern recognition
■Information security-related
- Information mathematics
- Cryptographic theory
- 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.
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 are engaged in research that integrates existing scientific methods, which explain the composition of data with mathematical models expressing human knowledge, 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 science grounded 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’ performance as in the past will be difficult. We are conducting research on realizing “soft” computers in which logical flexibility is introduced into their hardware structure. At the same time, 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 and dialogue 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 such as 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.
Data Science Program
In this program, students are trained to become data scientists who can analyze big data and contribute to the development of society.
Medical/Healthcare Information Coursework Model
■Statistics-related
- Descriptive and exploratory statistics
- Information statistics
- Data analysis exercises
■Medical/healthcare-related
- Medical/healthcare informatics
- Bioinformatics
- Healthcare
■AI-related
- Big data analysis
- 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
- Descriptive and exploratory statistics
- Information statistics
- Data analysis exercises
■Society and tourism information-related
- Society and tourism informatics
- Social policy/Behavioral science
- Application of VR/AR
■AI-related
- Big data analysis
- Statistical machine learning
- AI
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.).
Research Themes(Data Science Program)
Large-scale Genomic Data-based Predictive Modeling
We are developing mathematical models and algorithms for searching 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 development of algorithms makes use of extensive knowledge of mathematic statistics, biostatistics, genetics, and machine learning.
Overview of Nagasaki Prefecture Tourism Vitalization Support System
The figure below shows an information platform developed in cooperation with Nagasaki Prefecture and Nagasaki City for collecting and analyzing tourism-related big data. This system provides information for quick visualization, such as where tourists are staying and how long they stay in spots, in order to understand tourism trends. The information is based on smartphone log information and information available on the Web.
Model Selection and Statistical Inference
The figure below shows artificially created scatter plots of relationships between curved class grade (y), study time (x1), and height (x2). y seems proportional to x1 and independent of x2. Making these determinations by automatically judging from data is called model selection. The research theme here focuses on statistical inference, which includes exploring the significance of some extracted variables after carrying out model selection.
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 the stones assembled? What were inside the pyramids? And, how were they designed? For ancient Egyptians, the design and construction of pyramids solved an unknown problem. Unraveling this mystery by humanity today will offer important clues for solving our own yet-unknown problems.