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About the Faculty

What is Business Data Science?

Business Data Science is the study of applying information knowledge to solve social problems from a business perspective.

　Advances in information science are astonishing. For example, collecting and analyzing vast amounts of human behavioral data has drastically improved the accuracy of “future predictions.” The evolution of AI also carries a strong sense of transforming society significantly. However, data and AI alone remain mere information. To enrich our world through their application, a business perspective that captures human needs is essential. Mastering information and solving social problems from a business perspective — this is Business Data Science, one of today's most notable fields of study. And the place to pursue the forefront of this discipline is the Faculty of Business Data Science.

■ The Ideal Graduate Profile

Leaders Who Create Innovation with the Power of Business and Data Science

　Through four years of study, graduates develop “business skills,” “data science skills,” and “human skills,” becoming leaders who drive social innovation. We cultivate individuals who can dedicate themselves to creating new businesses and building “strong organizations”—either as business professionals who master data with ease or as data scientists deeply versed in business. This faculty opens the door to limitless career opportunities: government agencies, multinational corporations, and venture companies casting groundbreaking ideas into shape.

Capability cultivated by the Faculty of Business Data Science

◎Business Skills

Practical Skills to Create Business

　We cultivate the capability to create business by leveraging data science, such as developing new methods to streamline business operations or building entirely new ventures addressing social challenges. We also develop the vision and coordination skills to build teams where members can maximize their potential.

◎Data Science Skills

Ability to Grasp Human and Social Movements Through Statistics

　Students acquire the ability to interpret accumulated data, grasp the underlying factors behind human behavior and social phenomena, derive new insights, and apply these to solve business problems. While learning technologies such as programming, security, deep learning, and databases, students cultivate the skills to apply them to business.

◎Human Skills

Ability to Proactively Pioneer One's Own Life

　We cultivate the ability to perceive social challenges as personal issues, think through solutions based on knowledge and experience, and act. Furthermore, we aim to nurture individuals who can continuously learn and act to improve themselves in response to the evolution of business and data science, thereby pioneering their own paths in life.

■ Curriculum

We cultivate leaders who apply the theories and skills learned in practice and create innovation with the skills of business and data science.

　In this faculty, students study both “business” and “data science” broadly from foundational to applied and advanced areas. To ensure this knowledge and these skills are applicable to the real world, the curriculum emphasizes “active learning.” Over four years, small-group seminar courses are offered so that students tackle actual social challenges through collaboration with companies. For example, we plan to implement projects that utilize corporate data such as actual store data to engage in marketing practices and formulating management strategies. Through these hands-on experiences, students cultivate their ability to identify and solve problems, growing into “business data scientists” who can immediately contribute to the business world upon graduation.

● Distinctive Learning Features

Meticulous Education Beyond the Boundaries of Arts and Sciences

Students acquire foundational knowledge in both business and data science through intensive, small-group education (including seminars) in the first year
Advanced Educational Environment for Deepening Expertise

Practice-oriented specialized education delivered by a faculty of renowned domestic and international professors, including practitioners with extensive experience
Real-world Learning Connected to the Professional World

Practical learning utilizing real data through corporate partnerships and participation in industry-academia collaboration programs
Active Learning Courses that Foster Independent Learning

Practical learning to acquire problem-finding and problem-solving skills through the integration of business and data science

Faculty Members

Name	Takashi Washio
Title	Professor
Undergraduate School・Graduate School / Degree	Tohoku University Graduate School / Ph.D. in Engineering
Research Areas	Artificial Intelligence, Data Science

Name	Kohei Ichikawa
Title	Professor
Undergraduate School・Graduate School / Degree	Osaka University Graduate School / Ph.D. in Information Science
Research Areas	Distributed Systems, Machine Learning

Name	Mayumi Kamata-Itakura
Title	Professor
Undergraduate School・Graduate School / Degree	University of Tokyo Graduate School / Ph.D. Academic
Research Areas	Software Engineering, Requirements Engineering, Information Systems and Business

Name	Yukiko Kawai
Title	Professor
Undergraduate School・Graduate School / Degree	NARA Institute of Science and Technology / Ph.D. in Engineering
Research Areas	Data Engineering, Informatics

Name	Wataru Sunayama
Title	Professor
Undergraduate School・Graduate School / Degree	Osaka University Graduate School / Ph.D. in Engineering
Research Areas	Data Science

Name	Keiji Takai
Title	Professor
Undergraduate School・Graduate School / Degree	Osaka University Graduate School / Ph.D. in Engineering
Research Areas	Statistics

Name	Naoko Nitta
Title	Professor
Undergraduate School・Graduate School / Degree	Osaka University Graduate School / Ph.D. in Engineering
Research Areas	Artificial Intelligence, Multimedia Data Analysis

Name	Ken-ichi Fukui
Title	Professor
Undergraduate School・Graduate School / Degree	Osaka University Graduate School / Ph.D. in Information Science
Research Areas	Artificial Intelligence, Data Science

Name	Hideo Misaki
Title	Professor
Undergraduate School・Graduate School / Degree	Kobe University of Commerce Graduate School / Ph.D. in Business Administration
Research Areas	Business Administration

Name	Katsutoshi Yada
Title	Professor
Undergraduate School・Graduate School / Degree	Kobe University of Commerce Graduate School / Ph.D. in Business Administration
Research Areas	Management Information

Name	Ken Ishibashi
Title	Associate Professor
Undergraduate School・Graduate School / Degree	Kansai University Graduate School / Ph.D. in Informatics
Research Areas	Information Science

Name	Xiaokang Zhou
Title	Associate Professor
Undergraduate School・Graduate School / Degree	Waseda University Graduate School / Ph.D. in Human Sciences
Research Areas	Ubiquitous Computing, Big Data, Machine Learning, Cyber-Physical-Social Systems

Name	Shuhei Denzumi
Title	Associate Professor
Undergraduate School・Graduate School / Degree	Hokkaido University Graduate School / Ph.D. in Information Science
Research Areas	Algorithms and Data Structures

Name	Hiroyuki Nakazono
Title	Associate Professor
Undergraduate School・Graduate School / Degree	Doshisha University Graduate School / Ph.D. in Commerce
Research Areas	Innovation Management

Name	Ryo Nishide
Title	Associate Professor
Undergraduate School・Graduate School / Degree	Kansai University Graduate School / Ph.D. in Informatics
Research Areas	Ubiquitous Computing

Name	Matthew J. Holland
Title	Associate Professor
Undergraduate School・Graduate School / Degree	Nara Institute of Science and Technology / Ph.D. in Engineering
Research Areas	Machine Learning

Name	Yuki Maruno
Title	Associate Professor
Undergraduate School・Graduate School / Degree	Nara Institute of Science and Technology / Ph.D. in Engineering
Research Areas	Machine Learning, Biosignal Processing

Name	Mao Mukai
Title	Associate Professor
Undergraduate School・Graduate School / Degree	Kansai University Graduate School / Ph.D. in Commerce
Research Areas	Financial Accounting

Name	Makoto Morisada
Title	Associate Professor
Undergraduate School・Graduate School / Degree	Osaka University Graduate School / Ph.D. in Economics
Research Areas	Marketing

Name	Satoshi Suga
Title	Assistant Professor
Undergraduate School・Graduate School / Degree	Keio University Graduate School / Ph.D. in Engineering
Research Areas	Artificial Intelligence, Data Science, Multi-Agent Simulation

Name	Tetsuo Shiihashi
Title	Visiting Professor (CEO of Laboro.AI, Inc.)
Undergraduate School・Graduate School / Degree	University of Texas (USA)
Research Areas	Artificial Intelligence, Machine Learning

Name	Rie Nakamura
Title	Visiting Professor (Director of M3, Inc.)
Undergraduate School・Graduate School / Degree	Kansai University
Research Areas	Corporate Management, Startups, Digital Transformation (DX)

Name	Yutaka Matsuo
Title	Visiting Professor (University of Tokyo Graduate School of Engineering / Professor at Research into Artifacts, Center for Engineering)
Undergraduate School・Graduate School / Degree	University of Tokyo Graduate School / Ph.D. in Engineering
Research Areas	Artificial Intelligence, Deep Learning, Web Mining