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Researcher's Profile

Takehisa YAIRI

Artificial Intelligence


2019 Research book (PDF: 1.1MB)


1999.03 PhD, School of Engineering, The University of Tokyo (UTokyo)
1999.04 Research Assistant, RCAST, UTokyo
2001.07 Research Assistant, School of Engineering, UTokyo
2003.04 Lecturer, School of Engineering, UTokyo
2004.03 Lecturer, RCAST, UTokyo
2006.11 Associate Professor, RCAST, UTokyo
2009.04 Associate Professor, School of Engineering, UTokyo
2019.03 Professor, School of Engineering, UTokyo
2019.04 Professor, RCAST, UTokyo

Research Interests

While deep learning is attracting much attention these days, we are especially interested in unsupervised learning, which is one of main topics in machine learning research. An important purpose of unsupervised learning is to reveal latent structures or patterns such as clusters and low-dimensional intrinsic subspace behind the big data and to model the mechanism of the data generation.
We are also studying on algorithms of learning dynamical systems (LDS), which aims at identifying mathematical models of natural and artificial dynamical systems from observation data. Obtained models can be utilized for control and prediction of those systems. This topic is closely reated to control engineering as well to machine learning.
Furthermore, we are applying these techniques to health monitoring and anomaly detection of large-scale artificial systems such as artificial satellites and plants. The goal of our study is to make the world safer and more secure by these technologies.

A Health Monitoring Method for Artificial Satellites by Unsupervised Learning


artificial intelligence, machine learning, anomaly detection, fault diagnosis, probabilistic reasoning, learning dynamical systems

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