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Goto Lab
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The lab applies mathematical information science, AI, and data science to management problems.

AboutAbout the lab
Applying the theory of data and information to management problems.
Goto Lab studies the application of mathematical information science, AI (artificial intelligence), and data science to problems in industrial and management engineering.
The lab works on fundamental technologies such as information theory, machine learning, statistical models, and natural language processing.
It also pursues applied research, such as marketing analysis, business analytics, and analysis of purchase history data.
In particular, the lab studies management and information in the Internet age broadly, from fundamentals to applications.
Key terms
- Data science
- The discipline of analyzing large amounts of data with statistics and information technology to draw out insights
- Machine learning
- A mechanism by which computers automatically learn rules and patterns from large amounts of data
- Natural language processing
- Technology that lets computers process and analyze the language people use in everyday life
NewsLab news
Two undergraduate students received the Best Presentation Award at the Japan Industrial Management Association (JIMA) 2025 Autumn Conference
A master's student received the Department Award of the Department of Industrial and Management Systems Engineering
An undergraduate student received the Outstanding Student Award from the Japan Industrial Management Association
A fourth-year undergraduate student received the Best Presentation Award from the Japan Industrial Management Association
A graduate student received the Best Paper Award at the international conference APIEMS2025
ResearchResearch themes
Goto Lab conducts research on applied mathematical information science, management informatics, and data science. As a branch of industrial and management systems engineering, the lab values engineering that is genuinely useful in practice.
*Illustrative imageBusiness analytics
The lab studies techniques for analyzing the large-scale data that accumulates daily in business settings and using it for management. It also works on methods for analyzing big data that is high-dimensional and has diverse characteristics.
*Illustrative imagePattern recognition and machine learning
The lab studies how to realize on computers the abilities of pattern recognition and learning that humans excel at. It also applies them to the analysis of large-scale management and marketing data.
*Illustrative imageTechniques for analyzing diverse data
The lab studies techniques for automatically analyzing data in diverse formats, such as text data from social media and review sites, and image data. It also works on analysis of chat data within companies.
*Illustrative imageMarketing data analysis
The lab studies how to analyze the large-scale data that companies accumulate, such as POS data and web browsing history data, and use it for marketing measures and management decision-making.
MembersFaculty
The members of Goto Lab consist of faculty, doctoral, master's, and undergraduate students, a secretary, non-degree course students, and joint researchers.As of 2026
- ProfessorMasayuki Goto
VoicesStudent voices
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On a 4-point scale, ● marks where students' answers fall
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Hirai LabSchool of Creative Science and Engineering, Department of Industrial and Management Systems EngineeringManagement accounting, corporate valuation, accounting infor…The information on this page is compiled by the LabLog team from the lab's public information and interviews. For corrections or removal requests, please contact LabLog, not the lab.
Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Mylar Punched tape” Wtshymanski / CC BY-SA 3.0 (cropped)
- Business analytics: “Gold Pan” Nate Cull / CC BY 2.0 (cropped)
- Pattern recognition and machine learning: “Fingerprint” Zephyris / CC BY-SA 3.0 (cropped)
- Techniques for analyzing diverse data: “Beijing printing museum.wooden movable types” Popolon / CC BY-SA 4.0 (cropped)
- Marketing data analysis: “Vinyl collection at a record store (Unsplash)” Mr Cup / Fabien Barral iammrcup / CC0 (cropped)
- Related lab (Fukushige Lab): “Recycle Box Tokorozawa” tokorokoko / Public domain (cropped)
- Related lab (Munechika Lab): “Prototype kilogram replica” Japs 88 / CC BY-SA 3.0 (cropped)
- Related lab (Dan Lab): “Barabasi Albert 1000nodes” Keiichiro Ono / CC BY-SA 2.5 (cropped)
- Related lab (Hirai Lab): “Pine log cross-sections, Teutendorf” Radomianin / CC BY-SA 4.0 (cropped)
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