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Current (or future) research topics

Self-organization-based phenomena are commonly observed in nature on various spatiotemporal scales. Typically, they exhibit macroscopic patterns arising from local interactions between individual components.  In this context, I am attempting  to understand the fundamental principles underlying such emergent phenomena  based on simple mathematical models and develop “reasonable” control schemes for them. My field of research is interdisciplinary—at the crossroads between applied mathematics, mathematical biology, physics, control engineering, robotics, biology, medicine, social science, and sport science.

Decoding decentralized control mechanisms underlying animal locomotion

Animals exhibit astoundingly adaptive, robust, and versatile trends of locomotion  in response to their environment. Our goal is to clarify the essential mechanisms of animal locomotion based on mathematical modeling with a focus on decentralized control, which is characterized by emergent non-trivial behavior arising from coordination between simple individual components. My research interests include the locomotion of snakes, ophiuroids (brittle star), earthworms, centipedes, etc.

Designing super-survival systems by studying collectives of living organisms that exhibit altruistic behaviors

Several living organisms are capable of surviving in harsh environments by forming swarms. In these systems, 

individuals are often observed to exhibit altruistic behavior for the greater benefit of the overall swarm. For example, in bacterial biofilms, certain cells temporarily halt their uptake of nutrients to allow other starving cells to gain nourishment, which improves the survivability of the biofilm as a whole [1]. Further, while vampire bats cannot survive without food for more than three days, they often sustain themselves over several years by sharing food with each other in their community [2]. We aim to elucidate the control mechanisms underlying such altruistic behavior and design artificial agents with high survivability on this basis.

[1] J. Liu et al. Nature 523: 550-554 (2015) 

[2] G.S. Wilkinson, Nature 308: 181 (1984)

Understanding mechanisms of “heterogeneous cell swarm intelligence”

Living cells often collectively adapt to the environment and generate macroscopic functions that cannot be individually realized by any of the constituent cells. Cell collectives seem to possess a will or “intelligence” of their own. Heterogeneity of cells likely play an important role for the emergence of intelligence. We denote such behavior by the term, “heterogeneous cell swarm intelligence”, and aim to understand the underlying universal control mechanisms by focusing on several phenomena.

Understanding decentralized control mechanism of swarms consisting of "soft" individuals

The majority of conventional research on groups has traditionally considered the constituents of a group as particles or rigid bodies. However, in this study, we explore the principles of swarm intelligence that arise from the physical interaction among soft individuals. Therefore, we focus on tubificine worms, which possess long and flexible bodies that intertwine with each other to form blobs. These blobs adaptively change their shape while moving in complex real-world environments with narrow spaces and uneven ground. We aim to reveal how these worm blobs adaptively navigate in such complex real-world environments by conducting behavioral experiments, mathematical modeling, and simulations.

Decoding control and learning mechanisms underlying inter-personal sport activities

In activities related to inter-personal sports, certain skills are essential to communicate with others and develop oneself through friendly competition. However, control and learning mechanisms associated to these skills remain unclear. In this study, we focus on several activities, such as competitive dance, and aim to decode the underlying mechanisms via an integration of sport science, mathematics, and robotics.

Designing decentralized control schemes of traffic and swarm robotic systems

We aim to propose methods to control the flow of mobile agents (cars and robots) adaptively under various circumstances. For example, we study decentralized control of traffic signals that is capable of adapting to changes in traffic trends. We also study decentralized control of multi-agent transportation systems, in which each mobile agent transports objects or humans to their destinations (such as robots in warehouses, self-driving cars, and drones in flight) “rapidly, smoothly, and safely”.

Mathematical modeling of the relationship between the COVID-19 outbreak and economic activities

Acute respiratory syndrome caused by the coronavirus, COVID-19, is in the process of rapid transmission throughout the world, as of August, 2020. While avoiding close contact between humans is essential to mitigate the outbreak, such practice inevitably causes severe economic losses. This conundrum requires an urgent solution and the identification of strategies to mitigate outbreak while maintaining a basic level of economic activity is imperative. In this study, we aim to propose a mathematical model for the outbreak of COVID-19 by taking economic activities into account, with the intention of creating a platform to discuss solutions to the aforementioned dilemma.

Research on non-reciprocal-interaction-based model inspired by the process of friendship formation

The non-reciprocal-interaction-based model is a simple mathematical model for collective behavior, inspired by the process of friendship formation in human society, proposed by us in a previous study. Although the original motivation behind its development was mere curiosity, our simulations revealed various interesting non-trivial patterns depending on the parameters (for further details, please consult the following link on YouTube: In this study, we intend to identify prospective applications of this model.


Previous research topics

Density oscillator (or Saline oscillator)

The density oscillator is a simple system that exhibits self-sustained oscillation. It alternately exhibits up- and down-flow through a pipe which connects two containers filled with fluids of different densities. However, the mechanism of the flow reversal has not yet been fully understood. From the detailed measurements, we have found that flow reversal begins with an intrusion of fluid, which is followed by rapid growth. This process is definitely sensitive to the viscosities of the fluids, and as a consequence, the critical heights leading to flow reversal are clearly viscosity-dependent. These experimental results are explained by a simple model, derived by considering forces acting on a unit volume element located at the tip of the intrusion. Using this model, we can successfully explain the mechanism of flow reversal, which is the most essential process in a density oscillator.

Control of coupled-oscillator systems based on multi-linear feedback

Methods to control the dynamics of coupled oscillators have been developed owing to various medical and technological demands. In this study, we develop a method to control coupled oscillators in which the coupling function expressed in a phase model is regulated by the multilinear feedback. The present method has wide applicability because we do not need to measure an individual output from each oscillator, but only measure the sum of the outputs from all the oscillators. Moreover, it allows us to easily control the coupling function up to higher harmonics. The validity of the present method is confirmed through a simulation.

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