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Nonlinear Mathematics Lab [Graduate School of Information Science and Technology]
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This lab explores the nonlinear mathematics behind a wide range of phenomena.
AboutAbout the lab
Uncovering what lies behind phenomena with nonlinear dynamics
The Nonlinear Mathematics Lab studies diverse phenomena that appear in engineering, information, and biological systems by describing them with nonlinear mathematical models.
The lab works on understanding the nonlinear mathematics behind these phenomena and on developing methods for analyzing nonlinear mathematical models.
It also aims to apply nonlinear mathematics to engineering and information systems.
On the lab's website, it is also introduced under the name "Suzuki Lab."
Key terms
- Nonlinear dynamics
- The behavior of systems that evolve over time according to nonlinear rules. Rich behavior can emerge even from simple equations.
- Dynamical system
- A system that changes over time, described by maps or differential equations.
- Dimensionality reduction
- A framework for extracting a low-dimensional dominant skeleton from a high-dimensional nonlinear time-evolving system.
NewsLab news
A paper was published in Progress of Theoretical and Experimental Physics
A paper was published in Communications Physics
A paper was published in Journal of Neurophysiology
ResearchResearch themes
The lab studies the behavior of systems that evolve over time according to nonlinear rules, from the viewpoint of nonlinear dynamics. Targeting a wide range of phenomena modeled as nonlinear systems, such as the brain and nervous system and power systems, it contributes to understanding these phenomena and solving problems, while also exploring the unknown nonlinear dynamics hidden within them.
*Illustrative imageNonlinear Dynamics and Its Applications
The lab studies nonlinear dynamics that appear in large-scale dynamical systems and in dynamical systems with discontinuities. It models and analyzes phenomena from various fields, including biological systems such as the brain and nervous system, and power systems.
Dimensionality Reduction of Nonlinear Dynamical Systems and Its Applications
The lab develops and applies dimensionality reduction methods that extract a low-dimensional dominant skeleton from high-dimensional nonlinear time-evolving systems. It also works on extending these methods to hybrid dynamical systems and on analyzing collective phenomena such as rhythmic synchronization.
MembersFaculty
The members of the Nonlinear Mathematics Lab are faculty members, project researchers, visiting professors, visiting associate professors, and visiting faculty, administrative staff, doctoral, master's, and undergraduate students, and research students.As of 2026
- ProfessorHideyuki Suzuki
- Associate ProfessorSho Shirasaka
- Project Associate ProfessorWataru Kurebayashi
- Assistant Professor (Concurrent)Naoki Watamura
- Project Assistant ProfessorTakumi Minami
- Project Assistant ProfessorYusuke Miyajima
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Lorenz Attractor from Gauss-Legendre” Mgolden96 / CC BY-SA 4.0 (cropped)
- Nonlinear Dynamics and Its Applications: “Intermittent Lorenz Attractor - Chaoscope” Anders Sandberg from Oxford, UK / CC BY 2.0 (cropped)
- Related lab (Mathematical Systems Science Lab [Graduate School of Information Science and Technology]): “Frank-Wolfe Algorithm” Stephanie Stutz / CC BY 4.0 (cropped)
- Related lab (Bio-Information Measurement Lab [Graduate School of Information Science and Technology]): “Thermo - Finnigan LCQ Mass Spectrometer ( )” Kitmondo Marketplace / CC BY 2.0 (cropped)
- Related lab (Protein Crystallography Lab [Institute for Protein Research]): “Helix electron density myoglobin 2nrl 17-32” Dcrjsr / CC BY 3.0 (cropped)
- Related lab (Nano-Biophotonics Lab [Graduate School of Frontier Biosciences]): “Gold Nanoparticles” Tae Joon Cho Sherrie Elzey Vincent A. Hackley Stephen (San-Min) Lee Robert I. MacCuspie Julian Taurozzi De-Hao Tsai / Public domain (cropped)
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