Research Theme
Data Science, Business Analytics, Machine Learning and its Applications, and Marketing Data Analysis
Research Director
GOTO, Masayuki
Faculty of Science and Engineering, School of Creative Science and Engineering
Project Members
- GOTO, Masayuki Professor, Faculty of Science and Engineering, School of Creative Science and Engineering
- HASUIKE, Takashi Professor, Faculty of Science and Engineering, School of Creative Science and Engineering
- HIRAI, Hirohisa Professor, Faculty of Science and Engineering, School of Creative Science and Engineering
- HORII, Shunsuke Associate Professor, , Center for Data Science
- KOBAYASHI, Manabu Professor, Center for Data Science
- MATSUI, Tatsunori Professor, Faculty of Human Sciences, School of Human Sciences
- MORIGUCHI, Takeshi Professor, Faculty of Commerce, School of Commerce
- NAGATA, Yasushi Professor, Faculty of Science and Engineering, School of Creative Science and Engineering
- OHMORI, Shunichi Professor, Faculty of Science and Engineering, School of Creative Science and Engineering
- OHNO, Takahiro Professor, Faculty of Science and Engineering, School of Creative Science and Engineering
- SUKO, Tota Associate Professor, Faculty of Social Sciences, School of Social Sciences
- TAKEMOTO, Yasuhiko Professor, Faculty of Science and Engineering, School of Creative Science and Engineering
- HASUMOTO, Kyosuke
- IWANAGA, Jiro
- LUO, Xueming
- MIKAWA, Kenta
- MURAKAMI, Tomoaki
- NAKAGAWA, Keiichiro
- OGIHARA, Tairiku
- OKUBO, Masato
- SHIMIZU, Ryotaro
- SHIMIZU, Toshiaki
- SUZUKI, Hiroto
- SUZUKI, Satoshi
- TABATA, Tomoaki
- TARUISHI, Masato
- UEDA, Masao
- YAMASHITA, Haruka
- YANG, Tianxiang
- ZENG, Donglin
Research Keywords
Data Science Machine Learning Business Analytics Data Analytics Marketing Analysis Artificial Intelligence
Research Summary
With the spread of the Internet and the improvement of computer processing power, the intersection of “data “, “systems/analytical models ” and “employees” has become an important factor supporting corporate management and marketing activities. In order to respond to the changes of this era, it is an urgent and important problem in the business world to clarify how to design data analysis for business management systems and marketing measures, or what kind of systems and analytical models can be effective for decision-making. On the other hand, the data that can be used for business management decision-making and marketing measures is becoming increasingly large-scale and diverse in various directions, and new technologies such as generative AI and large language model are being paid attention. Under these backgrounds, the establishment of next-generation data science that takes these circumstances into account has become an urgent task.
This research institute conducts research on the theory and practice of the scientific handling of data, which is one of the key elements supporting company management and marketing activities, from both theoretical and practical perspectives. The data that can be used for business decision-making and marketing measures is becoming increasingly large-scale and diverse in various directions, so that we aim to establish next-generation data science based on these characteristics. In addition to the various methods used in the fields of traditional statistics and marketing science, we will actively introduce advanced analytical techniques from fields such as pattern recognition, machine learning and artificial intelligence, which have attracted attention in recent years, for basic models and analytical techniques for analyzing diverse data.
This will enable us to develop a methodology for analyzing business data for companies and systematize the analytical techniques of next-generation business analytics. Research activities in data science that target the above objectives should not be handled from a single research field, and an interdisciplinary approach is important. At this research institute, researchers from diverse fields of study such as science and engineering, commerce, social sciences, and human sciences gather to conduct the research activities from an extremely interdisciplinary perspective. Rather than simply focusing on fundamental and application studies in the fields of artificial intelligence
and machine learning, the scope of research also extends to the mechanisms for incorporating these into business activities. In addition, in order to develop methodologies and theories for the use of actual business data, we will actively promote joint research with companies in Japan, and conduct theoretical verification and empirical research using various actual data.
The Institute will continue the research project under the same name as the “Institute of Data Science” established in 2015. Since its establishment in 2015, the “Institute of Data Science ” has steadily increased its recognition, and the number of companies with which it conducts joint research has also increased. By continuing Institute of Data Science, it is expected that these joint research projects will continue, and new partnerships with other companies will be established. In addition, it is more effective in terms of PR and attracting visitors from outside the university to hold events such as the annual symposium under the same institute name. In addition, data science is a very hot research topic in today’s social environment, and it also has a significant social impact. For the above reasons, this research will continue to conduct
research activities under the name “Institute of Data Science”.