• Our new paper entitled "Synchronisation in two-dimensional damped-driven Navier–Stokes turbulence: insights from data assimilation and Lyapunov analysis" has been published in Journal of Fluid Mechanics. [link🔗]
  It has been selected as the cover image of the Journal of Fluid Mechanics. [link🔗] (Jan 2026) New!
• Our new paper entitled "Data-driven prediction of reversal of large-scale circulation in turbulent convection" has been published in Physical Review Fluids. [link🔗] (May 2025)
• Our new paper entitled "Reservoir computing with generalized readout based on generalized synchronization" has been published in Scientific Reports. [link🔗] (Dec 2024)
• Our new paper entitled "Stable reproducibility of turbulence dynamics by machine learning" has been published in Physical Review Fluids. [link🔗] (Oct 2024)
• I was honoured to receive the "Award for Distinguished Young Researcher in Fluid Mechanics" from the Japan Society of Fluid Mechanics. [link🔗] (Sep 2024)
• Our new paper entitled "Characterizing small-scale dynamics of Navier-Stokes turbulence with transverse Lyapunov exponents: A data assimilation approach" has been published in Physical Review Letters. [link🔗] (Dec 2023)
• Our new paper entitled "Fluid mixing optimization with reinforcement learning" has been published in Scientific Reports. [link🔗] (Aug 2022)

Fundamentals

Name: Masanobu INUBUSHI
Present position:

- Associate Professor, Department of Applied Mathematics, Tokyo University of Science

- Guest Associate Professor, Graduate School of Engineering Science, Osaka University

Email: inubushi (at) rs.tus.ac.jp

Academic Career

Mar 2024 - Mar. 2025: Visiting Scholar

@Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge

Apr 2021 - present position

Mar 2018 - Mar. 2021: Assistant Professor

@Fluid Mechanics Group, Graduate School of Engineering Science, Osaka University

Apr 2013 - Feb. 2018: Researcher

@NTT Communication Science Laboratories

Apr 2012 - Mar. 2013: JSPS Research Fellow (DC2)

@Research Institute for Mathematical Sciences (RIMS), Kyoto University

Education

Mar 2013: PhD in Mathematics

Research Institute for Mathematical Sciences (RIMS), Kyoto University

Supervisor: Prof. Michio Yamada and Assoc. Prof. Shin-ichi Takehiro

Thesis title: Covariant Lyapunov Analysis of Navier-Stokes Turbulence

Mar 2010: MSc in Mathematics

Research Institute for Mathematical Sciences (RIMS), Kyoto University

Mar 2008: BEng in Mechano-Aerospace Engineering

Department of Mechano-Aerospace Engineering, Tokyo Institute of Technology

Peer-reviewed papers

1. Masanobu Inubushi and Colm-cille P. Caulfield,
   "Synchronisation in two-dimensional damped-driven Navier–Stokes turbulence: insights from data assimilation and Lyapunov analysis",
   Journal of Fluid Mechanics 1027, A41 (2026).
   https://doi.org/10.1017/jfm.2025.11057 New!
2. Daigaku Katsumi, Masanobu Inubushi, and Naoto Yokoyama,
   "Data-driven prediction of reversal of large-scale circulation in turbulent convection",
   Physical Review Fluids 10, 053501 (2025).
   https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.10.053501
   
3. Akane Ohkubo and Masanobu Inubushi,
   "Reservoir computing with generalized readout based on generalized synchronization",
   Scientific Reports 14, 30918 (2024).
   https://www.nature.com/articles/s41598-024-81880-3
4. Satoshi Matsumoto, Masanobu Inubushi, and Susumu Goto,
   "Stable reproducibility of turbulence dynamics by machine learning",
   Physical Review Fluids 9, 104601 (2024).
   https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.9.104601
5. Masanobu Inubushi, Yoshitaka Saiki, Miki U. Kobayashi, and Susumu Goto,
   "Characterizing Small-Scale Dynamics of Navier-Stokes Turbulence with Transverse Lyapunov Exponents: A Data Assimilation Approach",
   Physical Review Letters 131, 254001 (2023).
   https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.131.254001
6. Yuto Iwasaki, Takayuki Nagata, Yasuo Sasaki, Kumi Nakai, Masanobu Inubushi, and Taku Nonomura,
   "Reservoir computing reduced-order model based on particle image velocimetry data of post-stall flow",
   AIP Advances 13, 065312 (2023).
   https://pubs.aip.org/aip/adv/article/13/6/065312/2894878/Reservoir-computing-reduced-order-model-based-on
7. Mikito Konishi, Masanobu Inubushi, and Susumu Goto,
   "Fluid mixing optimization with reinforcement learning",
   Scientific Reports 12, 14268 (2022).
   https://www.nature.com/articles/s41598-022-18037-7
   Featured in EurekAlert!
   "Mixing things up: optimizing fluid mixing with machine learning"
8. Masanobu Inubushi and Susumu Goto,
   "Transfer learning for nonlinear dynamics and its application to fluid turbulence",
   Physical Review E 102, 043301 (2020).
   https://arxiv.org/abs/2009.01407
   https://journals.aps.org/pre/abstract/10.1103/PhysRevE.102.043301
9. Takumi Yokosaka, Masanobu Inubushi, Scinob Kuroki, and Junji Watanabe,
   "Frequency of Switching Touching Mode Reflects Tactile Preference Judgment",
   Scientific Reports 10, 3022 (2020).
10. Masanobu Inubushi,
    "Unpredictability and robustness of chaotic dynamics for physical random number generation",
    Chaos: An Interdisciplinary Journal of Nonlinear Science 29, 033133 (2019).
    https://aip.scitation.org/doi/10.1063/1.5090177
11. Kosuke Takano, Chihiro Sugano, Masanobu Inubushi, Kazuyuki Yoshimura, Satoshi Sunada, Kazutaka Kanno, and Atsushi Uchida,
    "Compact reservoir computing with a photonic integrated circuit",
    Optics Express, 26(22) 29424-29439 (2018).
12. Makoto Tomiyama, Kazuto Yamasaki, Kenichi Arai, Masanobu Inubushi, Kazuyuki Yoshimura, and Atsushi Uchida,
    "Effect of bandwidth limitation of optical noise injection on common-signal-induced synchronization in multi-mode semiconductor lasers",
    Optics Express, 26(10), 13521-13535 (2018).
13. Takuma Sasaki, Izumi Kakesu, Yusuke Mitsui, Damien Rontani, Atsushi Uchida, Satoshi Sunada, Kazuyuki Yoshimura, and Masanobu Inubushi,
    “Common-signal-induced synchronization in photonic integrated circuits and its application to secure key distribution”,
    Optics Express, 25(21), 26029-26044 (2017).
14. Shoma Ohara, Andreas Karsaklian Dal Bosco, Kazusa Ugajin, Atsushi Uchida, Takahisa Harayama, and Masanobu Inubushi,
    "Dynamics-dependent synchronization in on-chip coupled semiconductor lasers",
    Physical Review E 96, 032216 (2017).
15. Masanobu Inubushi and Kazuyuki Yoshimura,
    "Reservoir Computing Beyond Memory-Nonlinearity Trade-off",
    Scientific Reports 7, 10199 (2017).
    https://www.nature.com/articles/s41598-017-10257-6
16. Tomohiro Ito, Hayato Koizumi, Nobumitsu Suzuki, Izumi Kakesu, Kento Iwakawa, Atsushi Uchida, Takeshi Koshiba, Jun Muramatsu, Kazuyuki Yoshimura, Masanobu Inubushi, and Peter Davis,
    "Physical implementation of oblivious transfer using optical correlated randomness",
    Scientific Reports 7, 8444 (2017).
    https://www.nature.com/articles/s41598-017-08229-x
17. Andreas Karsaklian Dal Bosco, Naoki Sato, Yuta Terashima, Shoma Ohara, Atsushi Uchida, Takahisa Harayama, and Masanobu Inubushi,
    "Random number generation from intermittent optical chaos",
    IEEE Journal of Selected Topics in Quantum Electronics, vol. 23, no. 6, pp. 1-8, (2017).
18. Nobumitsu Suzuki, Takuya Hida, Makoto Tomiyama, Atsushi Uchida, Kazuyuki Yoshimura, Kenichi Arai, and Masanobu Inubushi,
    "Common-signal-induced synchronization in semiconductor lasers with broadband optical noise signal",
    IEEE Journal of Selected Topics in Quantum Electronics, vol. 23, no. 6, pp. 1-10, (2017).
19. Andreas Karsaklian Dal Bosco, Syoma Ohara, Naoki Sato, Yasuhiro Akizawa, Atsushi Uchida, Takahisa Harayama, and Masanobu Inubushi,
    "Dynamics versus feedback delay time in photonic integrated circuits: Mapping the short cavity regime",
    IEEE Photonics Journal, Volume: 9, Issue: 2 (2017).
20. Kazusa Ugajin, Yuta Terashima, Kento Iwakawa, Atsushi Uchida, Takahisa Harayama, Kazuyuki Yoshimura, and Masanobu Inubushi,
    "Real-time fast physical random number generator with a photonic integrated circuit",
    Optics Express 25(6), 6511-6523 (2017).
21. Masanobu Inubushi, Kazuyuki Yoshimura, and Peter Davis
    "Noise robustness of unpredictability in a chaotic laser system: Toward reliable physical random bit generation”
    Physical Review E 91, 022918 (2015).
22. Masanobu Inubushi, Kazuyuki Yoshimura, Kenichi Arai, and Peter Davis
    “Physical random bit generators and their reliability: focusing on chaotic laser systems”
    Nonlinear Theory and Its Applications (invited paper), IEICE, vol. 6 no. 2 (2015).
23. Masanobu Inubushi, Shin-ichi Takehiro, Michio Yamada
    “Regeneration cycle and the covariant Lyapunov vectors in a minimal wall turbulence''
    Physical Review E 92, 023022 (2015).
24. Masanobu Inubushi, Miki U Kobayashi, Shin-ichi Takehiro, and Michio Yamada
    “Covariant Lyapunov Analysis of Chaotic Kolmogorov Flows”
    Physical Review E 85, 016331 (2012).

Peer-reviewed proceedings
1. Masanobu Inubushi and Susumu Goto
   Transferring Reservoir Computing: Formulation and Application to Fluid Physics,
   Lecture Notes in Computer Science 11731, 193, Springer (2019). https://link.springer.com/chapter/10.1007/978-3-030-30493-5_22
2. Mitsumasa Nakajima, Masanobu Inubushi, Takashi Goh, and Toshikazu Hashimoto
   Coherently Driven Ultrafast Complex-Valued Photonic Reservoir Computing, Proceedings Conference on Lasers and Electro-Optics, page SM1C.4 (2018). https://www.osapublishing.org/abstract.cfm?URI=CLEO_SI-2018-SM1C.4
3. Masanobu Inubushi, Miki U Kobayashi, Shin-ichi Takehiro, Michio Yamada
   Covariant Lyapunov Analysis of Chaotic Kolmogorov Flows and Time-correlation Function,
   Procedia IUTAM, 5, 244-248 (2012).
   https://www.sciencedirect.com/science/article/pii/S2210983812000934

Book chapters

1. Masanobu Inubushi, Kazuyuki Yoshimura, Yoshiaki Ikeda, and Yuto Nagasawa,
   On the Characteristics and Structures of Dynamical Systems Suitable for Reservoir Computing,
   Chapter 5, Reservoir Computing -Theory, Physical Implementations, and Applications-, Kohei Nakajima and Ingo Fischer (Eds.), Springer (2021).New!
   [link]