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Statistical Analysis Lab
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A lab that uses mathematics to clarify the statistical properties of data analysis methods.
AboutAbout the lab
Understanding the "why" of data analysis through mathematics.
The Statistical Analysis Group (Terada Lab) is grounded in mathematical statistics and conducts research aimed at both a mathematical understanding of modern data analysis methods and their application to real-world problems.
The lab emphasizes not only learning how to use data analysis methods, but also understanding why a method is effective and what its limitations are, so that students gain the expertise to use these methods well.
The lab was newly launched in April 2026.
Key terms
- Mathematical statistics
- The field that theoretically examines what can be concluded from data, using probability and mathematics
- Deep learning
- A machine learning method that uses multilayer neural networks to learn patterns from data
- Sparse estimation
- An estimation method that builds a model by selecting only the truly necessary elements from among many candidates
NewsLab news
A doctoral student received the Outstanding Presentation Award at the Spring Meeting of the Japan Statistical Society
A doctoral student received the ISI Tokyo Meeting Commemorative Encouragement Award from the Japan Statistical Society
A doctoral student received the Outstanding Report Award at the Joint Conference of Statistical Societies of Japan
ResearchResearch themes
This lab aims to understand data analysis methods deeply, including their statistical properties and not only how to use them. To that end, it works on the statistical theory of the methods themselves and on interdisciplinary research with the natural sciences.
Statistical Theory of Data Analysis Methods
The lab develops pioneering data analysis methods and computational methods, including deep learning, unsupervised learning, high-dimensional and infinite-dimensional data analysis, operator learning, and sparse estimation, and clarifies their statistical properties.
*Illustrative imageInterdisciplinary Research with the Natural Sciences
The lab conducts interdisciplinary research with fields such as seismology (e.g., probabilistic assessment of Nankai earthquakes), physics (gravitational wave observation), neuroscience (fMRI data analysis), and sports medicine (identifying injury risk).
MembersFaculty
The members of the Statistical Analysis Group (Terada Lab) consist of faculty members and doctoral and master's students.As of 2026
- ProfessorYoshikazu Terada
- LecturerShogo Nakakita
VoicesStudent voices
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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: “Deep Learning” Sven Behnke / CC BY-SA 4.0 (cropped)
- Interdisciplinary Research with the Natural Sciences: “Gravitational Waves (GravitationalWaves)” NOIRLab / CC BY 4.0 (cropped)
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