Energy-efficient information processing
We are trying to develop effective methods to downsize cognitive networks for low power consumption. Optimizing and downsizing cognitive computational systems for intelligent information processing is critically important for reducing power consumption and heat generation. We will explore fundamental methodologies to systematically transform the structure of cognitive networks to be more compact without affecting their computational performance. This research is a collaborative project with Japan IBM, entitled "Next Generation Nano-Micro Devices and Systems for Energy-Efficient Information Processing."
Mathematical studies on medical and social systems
It is becoming possible to obtain real data on medical and social systems due to the developments of sensor devices and measurement techniques. Based on these data, we are trying to construct mathematical models for cancer growth, spreading epidemics, and opinion formation. We aim to propose effective control strategies for solving medically and socially important problems and improving quality of life.
- Intermittent hormone therapy for prostate cancer
- Epidemic model with seasonal forcing
Dynamical robustness of complex networks
Networked systems are ubiquitous in the world. Complex topological structures are found in power networks, traffic networks, and biological networks. Networking brings about merits such as improved convenience and cost reduction, but accompanies a risk that a partial failure causes a breakdown of the whole system. We are investigating how network robustness depends on network structure, dynamics, and element interactions. Our aim is to develop a design method of robust networks and a recovery method of damaged networks.
- Dynamical robustness of oscillator networks
Fundamental theory of complex systems dynamics
We are developing fundamental methodologies for understanding and analyzing complex systems. Depending on the condition, system behavior can change from order to disorder, from simple to complex, and from regular to irregular. We aim to understand the mechanism of such qualitative changes of system behavior. We formulate the sigularity at a qualitative change based on bifurcation theory and phase transision theory.