Month: October 2019

Kazuhiro Sato

Posted on by keisu-editor

Profile

Kazuhiro SATO

Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo
Lecturer

Room 434, 7-3-1 6 Hongo, Bunkyo-ku, Tokyo 113-8656
Tel: +81-03-5841-6934

E-mail：kazuhiro@mist.i.u-tokyo.ac.jp

[Personal Site]

Biography

March 2009 Bachelor of Engineering from Undergraduate School of Informatics and Mathematical Science, Kyoto University
March 2011 Master of Informatics from Department of Applied Mathematics and Physics, Graduate School of Informatics, Kyoto University
March 2013 Ph. D. in Informatics from Department of Applied Mathematics and Physics, Graduate School of Informatics, Kyoto University
April 2014 Project Researcher, Graduate School of Informatics, Kyoto University
April 2017 Specially Appointed Assistant Professor, Kitami Institute of Technology
April 2018 Assistant Professor, Kitami Institute of Technology
October 2019 Lecturer, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo

Research Topics

I am especially interested in solving control systems problems using methods of different fields such as optimization and machine learning. The following three topics are main research subjects.

  1. Applications of optimization theory to control systems theory: We study what control systems problems can be solved using Riemannian optimization, proximal algorithm, submodular optimization, and so on.
  2. Applications of control systems theory to optimization theory: We study what optimization problems can be efficiently solved using control systems theories such as hybrid systems, passivity, and so on.
  3. Data-driven modeling for controlling systems: We study efficient modeling methods for controlling systems from time series data using optimization, machine learning, numerical analysis, and so on.

 

Selected Publications

  • K. Sato:Riemannian optimal model reduction of linear port-Hamiltonian systems,
    Automatica, Vol. 98, pp. 428–434, 2018.
  • K. Sato and H. Sato: Structure preserving H^2 optimal model reduction based on Riemannian trust-region method, IEEE Transactions on Automatic Control, Vol. 63, No. 2, pp. 505-511, 2018.
  • K. Sato: Riemannian optimal control and model matching of linear port-Hamiltonian systems,
    IEEE Transactions on Automatic Control, Vol. 62, No. 12, pp. 6575-6581, 2017.