Department of Interdisciplinary Statistical Mathematics

The Interdisciplinary Research Division in Statistical Mathematics focuses on complex phenomena using advanced statistical and mathematical techniques. Aiming to bridge theoretical advances in mathematical statistics with practical applications, the division strives to uncover new insights and address real-world challenges in three key areas: humanities and social sciences, biological and medical sciences, and engineering and information sciences. Each area has its own specialized group.

The Humanities and Social Sciences Group develops statistical and mathematical methods to transform humanities and social sciences. This group not only advances economic, financial, and social survey statistics but also explores language, psychology, and education. By analyzing data from diverse sources, modeling for information extraction, and studying decision-making, the group seeks to elucidate hidden structures in social phenomena, augment society’s understanding of such phenomena, and enhance predictive accuracy.

The Life Sciences and Environmental Sciences Group applies statistical mathematics to tackle complex problems in biology, medicine, and environmental sciences. Techniques such as probability theory, mathematical modeling, and statistical optimization are utilized to address vital issues, including biodiversity conservation, ecosystem sustainability, environmental management, disease mechanisms, and medical technology development. This group creates new theories and practical solutions that contribute to society.
　

The Sciences/Engineering/Informatics Group employs advanced statistical mathematical methods in applied research in physical science, engineering, and information science. To advance the theories and methodologies of statistical mathematics to solve engineering problems and foster technological innovation, this group investigates key scientific issues in these fields through data assimilation, statistical machine learning, spatiotemporal data analysis, and differential privacy.