Masanobu Inubushi

Homepage URL (1)： https://www.rs.tus.ac.jp/~inubushi/

Research field (2)： Applied mathematics and statistics , Mathematical physics and basic theory

Research keywords (4)： Fluid Mechanics , Dynamical System Theory , Machine Learning , リザバーコンピューティング

Research theme for competitive and other funds (7)：

2024 - 2029 物理と数学の協働による乱流クロージャー問題解決に向けた機械学習理論の創出
2022 - 2027 光多重化によるフォトニックコンピューティングデバイスの変革
2022 - 2027 不安定性に着目した流体力学系の分解とデータ駆動型手法への応用
2020 - 2024 Control of turbulence by additives: principles in terms of the hierarchy of coherent structures
2020 - 2023 Inference of the energy dissipation rate and construction of turbulence model by machine learning

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Papers (24)：

Mikito Konishi, Masanobu Inubushi, Susumu Goto. Fluid mixing optimization with reinforcement learning. Scientific Reports. 2022. 12. 1
Masanobu Inubushi, Kazuyuki Yoshimura, Yoshiaki Ikeda, Yuto Nagasawa. On the Characteristics and Structures of Dynamical Systems Suitable for Reservoir Computing. Natural Computing Series. 2021. 97-116
Masanobu Inubushi, Susumu Goto. Transfer learning for nonlinear dynamics and its application to fluid turbulence. Physical Review E. 2020. 102. 4
Takumi Yokosaka, Masanobu Inubushi Scinob, Kuroki Junji Watanabe. Frequency of Switching Touching Mode Reflects Tactile Preference Judgment. Scientific Reports. 2020. 10. 3022. 1-16
Masanobu Inubushi. Unpredictability and robustness of chaotic dynamics for physical random number generation. Chaos: An Interdisciplinary Journal of Nonlinear Science. 2019. 29. 3. 033133-033133

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MISC (24)：

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Books (2)：

Reservoir computing : theory, physical implementations, and applications
Springer 2021 ISBN:9789811316869
On the Characteristics and Structures of Dynamical Systems Suitable for Reservoir Computing
2019

Lectures and oral presentations (12)：

Coherently Driven Ultrafast Complex-Valued Photonic Reservoir Computing
(CLEOR: Conference on Lasers and Electro-Optics 2018)
Reservoir Computing Beyond Memory-Nonlinearity Trade-off
(The 37th Dynamics Days Europe 2017)
A numerical study on the role of nonlinearityof activation function in reservoir computing
(The 36th Dynamics Days Europe 2016)
Memory capacity and time scales in delay dynamical systems for reservoir computing
(The 35th Dynamics Days Europe 2015)
Noise-robustness of physical random bit generation
(The 35th Dynamics Days Europe 2015)

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Education (2)：

2008 - 2013 Kyoto University Graduate School of Science Division of Mathematics and Mathematical Sciences
2004 - 2008 Tokyo Institute of Technology Department of Mechano-Aerospace Engineering

Professional career (1)：

Work history (5)：

2021/04 - 現在 Osaka University Graduate School of Engineering Science Department of Mechanical Science and Bioengineering Division of Nonlinear Mechanics
2021/04 - 現在 Tokyo University of Science Faculty of Science, Division 1 Department of Applied Mathematics
2018/03 - 2021/03 Osaka University Graduate School of Engineering Science Assistant Professor
2013/04 - 2018/02 NTT Communication Science Laboratories, NTT Corporation Researcher
2012/04 - 2013/03 Kyoto University Research Institute for Mathematical Sciences

Committee career (5)：

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