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- Kiyoshi KOTANI
Researcher's Profile
- Associate Professor
- Kiyoshi KOTANI
Biography
March 2003 | Dr.Eng., Graduate School of Engineering, The University of Tokyo (UTokyo) |
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April 2003 | Assistant Professor, Graduate School of Information Science and Technology, UTokyo |
November 2006 | Lecturer, Graduate School of Frontier Science, UTokyo |
September 2011 | Associate Professor, Graduate School of Frontier Science, UTokyo |
April 2014 | Associate Professor, Graduate School of Engineering, UTokyo |
August 2014 | Associate Professor, RCAST, UTokyo |
April 2023 | Professor, Graduate School of Frontier Sciences, UTokyo |
Research Interests
Recent advances in experimental and analytical techniques have revealed that biological systems are precisely organized to do various functions better than we had imagined. We have been developing theories for dynamical systems and methods of measurement in order to elucidate the underlying mechanisms of complex biological phenomena. We also apply the basic biological findings to a wide range of fields, including diagnosis, rehabilitation, and human interfaces. Specifically, we have conducted studies on:
(a) Developing theoretical methods for nonlinear and time-delayed stochastic systems on complex networks, (b) Understanding the functions of working memory and recognition using multi-scale brain models and noninvasive brain measurements, and (c) High-speed brain-machine interfaces using virtual reality.
The main topics for our research group are as follows:
- Mathematical theory for dynamical systems in biology
- Dynamics of gene-regulatory networks with time-delayed interactions
- Elucidating information processing in the brain using multi-scale brain models and noninvasive brain measurements
- A signal processing method for precisely evaluating blood flow in the brain
- Robotic ultrasound examinations to prevent lifestyle related diseases
- A support system for manufacturing workers using non-invasive evaluation of the autonomic nervous system
- Novel brain-machine interfaces based on augmented reality
Keywords
nonlinear dynamics, statistical physics, biomedical signal processing, human interface