Naoya Takeishi is a postdoctoral researcher working at RIKEN Center for Advanced Intelligence Project (AIP), Japan. He received his Ph.D. in Engineering from the Department of Aeronautics and Astronautics, the University of Tokyo in 2018. His research interests include machine learning with domain knowledge and data-driven analysis of dynamical systems.
Statistical machine learning with domain knowledge
- Efficient incorporation of prior knowledge given by domain experts, such as relational constraints, simulators, and side information, into statistical machine learning.
Data-driven analysis of dynamical systems
- Analysis of dynamical systems and time-series data based on the operator-theoretic view and its data-driven method, such as dynamic mode decomposition (DMD).
- Application of anomaly detection techniques based on machine learning to engineering systems, such as artificial satellites, vehicles, and power plants.
Visual SLAM for space exploration
- Simultaneous estimation of the shape and motion of a target celestial body (e.g., asteroid) as well as the position and attitude of a spacecraft.