\u3000”Statistical science” is a field that applies probability theory to develop optimal statistical methods for identifying the characteristics of populations based on observed data. In recent years, “data science” – closely linked to big data and artificial intelligence (AI) – has drawn increasing attention. At the core of these emerging disciplines lies statistical science (or statistical theory), which has gained renewed importance.
\u3000In response, our university must establish a research infrastructure that not only leads Japan but also contributes globally to the advancement of data science. However, research in data science spans a wide range of fields. Tokyo University of Science is actively pursuing excellence in this area, aiming to earn global recognition. Tokyo University of Science is place to many faculty members who specialize in statistics, with experts located across all its campuses. Notably, Tokyo University of Science stands out in Japan for having an exceptionally large number of researchers in mathematical statistics, a field focused on the theoretical foundations of statistical inference. We also have a strong track record in medical statistics, having previously offered specialized programs for working professionals.
\u3000With these strengths, we aim to establish a vibrant research hub that brings together experts across campuses and departments to collaborate on innovative projects unique to Tokyo University of Science. This research department will unite researchers from diverse fields who share an interest in foundational theory. Our goal is to elevate the study of essential statistical theories and methodologies, foster the creation of new theories, and pioneer emerging fields in the era of data science.<\/p>\n\n\n\n
This research department is roughly divided into three groups that conducts research in the following fields.<\/p>\n\n\n\n
\u3000The \u201cmultivariate analysis group\u201d comprises faculty members from Kagurazaka, Katsushika, and Noda Campuses and visiting associate professors. Focusing on the existing research themes of each faculty member, \u201cmultidimensional missing data analysis,\u201d \u201chigh-dimensional data analysis,\u201d \u201crandom matrix theory,\u201d and \u201cdimension reduction method,\u201d we will conduct research with a view to developing the Applied Statistics Research Group. The \u201cstatistical model group\u201d comprises faculty members from Kagurazaka and Noda Campuses and conducts research on topics such as \u201cstatistical modeling and model selection,\u201d \u201cnonparametric methods,\u201d and \u201ccontingency table analysis.\u201d The method, handled by the Mathematical Statistics Basis Group, has a clear theoretical background and acts as a white box. However, the method of solving a \u201creal-world problem\u201d has a black-box aspect, such as in heuristics and deep learning. In constructing the theory of AI and data science, how to clarify the black-box-like solution of the latter using the methodologies of the former, as well as other methodologies, will be asked.<\/p>\n\n\n\n
\u3000In the field of \u201cmedical statistics (biostatistics),\u201d the faculty members of Katsushika Campus will conduct research activities related to the methodology of research design and data analysis, focusing on medical research. In particular, the Department of Information and Computer Technology, Faculty of Engineering, has an excellent and internationally acclaimed research track record, and new research is expected through intra and inter-group interactions. \u201cMathematical \ufb01nance (time-series analysis)\u201d will be studied mainly by the faculty members from Katsushika Campus, and research on the development of educational methods and systems via quantitative analysis in \u201ceducational engineering\u201d will be conducted mainly by the faculty members from Kagurazaka Campus. Additionally, in recent years, the \ufb01eld of \u201csports statistics\u201d has been gaining attention, and the faculty members from Noda Campus and visiting associate professors are actively conducting research in this field. Moreover, we plan to conduct joint research involving student exchange programs. Regarding the \u201cstatistical machine learning\/mathematical optimization \ufb01eld,\u201d research on \u201cnatural-language processing that integrates statistical\/machine learning and symbolic modeling,\u201d \u201clarge-scale nonlinear optimization problems related to big-data analysis and machine learning,\u201d and \u201cstatistical methods for computer-based data mining and pattern recognition\u201d will be conducted mainly by the faculty members from Kagurazaka Campus.<\/p>\n\n\n\n
\u3000The Data Analysis Team, established in fiscal year 2025, was created to address the increasing need for precise and flexible analytical methods in today\u2019s society, where a wide variety of complex data is generated and accumulated daily. The team aims to strengthen collaboration with external partners through the Data Science Center, which facilitates joint research with companies and research institutions. To achieve this, the team adopts a flexible structure that allows researchers with the appropriate expertise to be assembled according to the specific needs of each project.
\u3000While the Mathematical Statistics Group focuses on the theoretical development of statistical methods, and the Applied Statistics Group emphasizes practical applications in areas such as medicine, finance, education, and sports, the Data Analysis Team bridges the gap between theory and application. Its primary objective is to develop and apply statistically sound, interpretable methods to analyze complex real-world data.
\u3000The team actively engages in cross-disciplinary challenges, utilizing advanced techniques such as statistical modeling in big data environments, interpreting machine learning and deep learning results, causal inference, Bayesian estimation, and data visualization. Researchers from various campuses and departments collaborate to form optimal project teams, providing a high degree of flexibility to meet diverse research needs.
\u3000Building on Tokyo University of Science\u2019s long-standing strength in mathematical statistics, the Data Analysis Team aspires to become a central hub for exploring the role of statistical analysis in supporting scientific decision-making amid real-world complexities.<\/p>\n","protected":false},"excerpt":{"rendered":"
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