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Artificial Intelligence Yairi Laboratory

Artificial intelligence for revealing data generating mechanisms and monitoring health status of systems

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.

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. Furthermore, we are applying these techniques to health monitoring and anomaly detection of large-scale artificial systems such as artificial satellite. The goal of our study is to make the world safer and more secure, with artificial intelligence.

Simultaneous localization and mapping by non-linear dimensionality reduction
Simultaneous localization and mapping by non-linear dimensionality reduction
Estimation of asteroid shape model and spacecraft poses from image sequence
Estimation of asteroid shape model and spacecraft poses from image sequence
Anomaly detection for artificial satellite telemetry by unsupervised learning
Anomaly detection for artificial satellite telemetry by unsupervised learning

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  • Takehisa YAIRI
  • Specialized field:Artificial intelligence, machine learning, aerospace engineering, prognostics, health monitoring
<As of May 2020>

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