In today’s increasingly complex and diversified digital society (DX society), solving problems in each domain requires going beyond traditional disciplinary boundaries. It calls for integrative education and research practices that combine statistical science, AI, machine learning, mathematical science, computer science, and communication science?and at times even philosophy of science and mathematical logic.
At Tohoku University, under our “Vision 2030” (updated edition) and the “Connected University Strategy,” we have emphasized the promotion of data-driven research and open science. In alignment with this, our Graduate School of Information Sciences has advanced interdisciplinary education and research in data science, involving not only the natural and engineering sciences, but also the humanities and social sciences.
The Center for Statistical Science aims to serve as a hub for cutting-edge education and research, fostering collaboration not only within the Graduate School of Information Sciences, but also with universities and research institutions across Japan and internationally.
Seminars are held to learn the latest knowledge and application examples of statistical science. Through lectures and discussions by experts, we will deepen their practical understanding the statistical science and data science.
Lectures are held from time to time on the development of new theories and models in statistical science, mainly by well-known foreign scholars, as well as on major global issues (such as the COVD-19 pandemic). The lectures are attended not only by experts but also by the general public, providing an opportunity for wide-ranging discussions.
This is a proposed research project in which researchers in various research fields invite members each other to discover cutting-edge research themes and develop new data analysis methods.
Building on the outcomes of collaborative projects and academic seminars, we will establish a virtual network, the "Researchers' Connected Society," as a dynamic global platform. Centered on the Center for Statistical Science, this network will connect researchers from around the world to engage in discussions on cutting-edge research topics.
From the standpoint of statistical science, we will give advice how to costruct an analytical research system for each stage (first: consultation on survey and data measurement plan, second: support for analysis model selection and analysis, third: interpreting and summarising results).
For master's students, we offer one- to two-month study abroad and internships. Students receive direct guidance from experts in statistical science and information science, and enhance their academic knowledge and practical skills through actual projects.
Based on the pillars of "Specialized Education Program in Statistical Science" and "Long-term Internship", linked to existing programs at Tohoku University. we will create an environment in which students can get systematic learning of statistical science with practical experience.
We have established a new "Model Curriculum for Statistical Science" that allows students to systematically study statistical science. We will build a framework that allows students to learn step-by-step from the basics to the advanced contents, and support the acquisition of specialized knowledge and practical skills.
We support the development of teaching materials to promote specialized education in statistical science. We incorporate the latest statistical methods and data analysis techniques to enhance practical learning. We will build a step-by-step learning framework to help you acquire specialized knowledge and practical skills.
The recent development of generative AI has been remarkable, with speed and capabilities far exceeding our expectations. One of the ultimate goals of the Center for Statistical Science is to create a statistical science version of AI of AI (AoA) that brings together the achievements and wisdom of the fields of statistical science and data science. In collaboration with researchers in various fields such as human and social sciences, natural sciences, agriculture, engineering, medicine, pharmacology, and health sciences, it proposes the optimal data required for data analysis in response to research questions raised by the research, and automatically selects, analyzes, evaluates, and interprets data, using analysis methods from classical to cutting-edge technologies. If we could create a system that does not make each process a black box, but proposes it while clearly stating the scientific basis! I think.
