KYUSHU UNIVERSITYInstitute of Mathematics for Industry

We successfully held the Industrial Mathematical Statistics Tutorial on December 12–13, following last year’s event. A total of 44 participants from diverse backgrounds—including professionals from industry and government, researchers, graduate students, and undergraduates—joined the tutorial. In the post-event survey, many participants shared positive feedback, such as, “I gained new knowledge of statistics and data analysis as well as practical skills,” and “The clear and engaging lectures were refreshing and fascinating.” On the other hand, some expressed a desire for “more concrete examples,” which we will take into consideration for future improvements. We sincerely hope that the insights gained through this tutorial will be of some benefit to your work or research.

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[Summary of the event]

Summary
Continuing from 2023, we will be holding an “Industrial Mathematical Statistics Tutorial” where you can learn from experts in statistics and data science mathematics.
As the need for research based on academic foundations of mathematics, data science, and AI is rapidly increasing in the social issues of “decarbonization,” “medical care and health,” and “environment and food” promoted by Kyushu University, the Industrial Mathematical Statistics Research Division, established in April 2022 at the Institute for Mathematics for Industry (IMI), aims to form a cross-disciplinary mathematical foundation with statistics at its core, deepen the theory of statistics, contribute to solving various problems in society, industry, and various fields, and develop young core statistical talent.

Date
December 12 – 13, 2024

Venue
744 Motooka Nishi-ku, Fukuoka, Japan
INAMORI Hall, INAMOR CENTER, Ito Campus, Kyushu University

Organized by   Division of Industrial and Mathematical Statistics, IMI, Kyushu University
Co-organized by Data-Driven Innovation Initiative, Kyushu University
         Education and Research Center for Mathematical and Data Science

Number of applicants: 100
If there are too many applicants, the number will be determined by lottery.*

Free of charge

Please register in advance.
The deadline for pre-registration is Saturday, November 30, 2024.

Target group
+People in industry and government whose work requires knowledge and skills in data science and related fields.
+Researchers, graduate and undergraduate students who need statistics in their research.

Learning from Math Experts	Learn practical knowledge and statistical mathematics theory directly from IMI faculty.
Catching up on the latest trends	Exposure to cutting-edge topics such as topological data analysis.
Promoting understanding of statistical mathematics	Provides a wide range of knowledge from basic to advanced topics in statistical mathematics.
Responding to the Data Driven Era	Cultivate the ability to use data science and statistics to address industry issues.
Training the next generation of engineers	Cultivate next-generation engineers who can play an active role in problem-solving by utilizing data and statistics.

Program

	Topic	Level	Lecturer
December 12 (Thu) 10:00 AM – 10:30 AM	Front Desk (INAMORI Hall, INAMOR CENTER)
December 12 (Thu) 10:30 AM – 12:00 PM	Student‘s t-test and its mathematical background	Beginner	HIROSE, Masayo
December 12 (Thu) 1:00 PM – 2:30 PM	Statistical Inference, Asymptotic Theory	Beginner	HIROSE, Kei
December 12 (Thu) 2:50 PM – 4:20 PM	Robust Estimation Methods against Outliers	Between Beginner and Intermediate	KURATA, Sumito
December 13 (Fri) 10:30 AM – 12:00 PM	Bayesian Linear Regression, Bayesian Information Criterion	Between Beginner and Intermediate	TOKUDA, Satoru
December 13 (Fri) 1:00 PM – 2:30 PM	Topological Data Analysis	Between Intermediate and Advanced	IKE, Yuichi
⏩ Some content may be omitted or added depending on lecture time constraints. The lectures will be conducted in Japanese only.

Beginner: Some understanding of simple probability calculations, linear algebra, and calculus is desirable
Intermediate: It is desirable to have studied estimation and testing.
Advanced: It is desirable to have a passing knowledge of mathematical statistics.

You could view the archive here.

Contact information
Administrative Office, Math. &IMI, Kyushu University