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学术报告(Ruili Wang)

Modelling Complex Systems

报告人 :   Dr. Ruili Wang, Senior Lecturer,
           Computer Science School of Engineering of Advanced Technology,
           Massey University, New Zealand
地点 :     蒙民伟楼311会议室
时间 :     9月7号下午4:00

Abstract:
Traffic and transport can be observed in many complex systems and at almost
all levels of nature (e.g., from microscopic motor proteins to macroscopic
objects like vehicles) and proved to be a rewarding research topic in the last
few years.
Our research studies the dynamics of the traffic in self-driven many-particle
systems. Self-driven many-particle systems contain many interacting particles
(e.g., molecular protein motors and cars). Also, they can be kept out of
equilibrium due to either self-driven or external fields. In this regard, such
systems are also known as driven diffusive systems. We particular interested
in self-driven diffusive systems in which traffic flow of particles can be
considered as taking place on ``tracks''. Examples include the directed
movement of motor proteins (e.g., Kinesin and Dynein) along cytoskeletal
filaments (i.e., microtubules or actin filaments). Motor protein traffic is
one of the topics in System Biology.
Our research is conducted in two approaches: theoretical analysis (e.g., mean
field approach and domain wall theory) and Monte Carlo simulations. The
results of these two approaches can verify each other. In this seminar, we
will discuss some our progresses in the field and potential future work.

Biography:
Ruili Wang received his PhD in Computer Science from Dublin City University
and he is a Senior Lecturer in Computer Science at Massey University, New
Zealand. His research interests include Modeling Complex Systems and
intelligent Systems. He is an associate editor and a member of the editorial
boards of The IEEE Intelligent Informatics Bulletin, International Journal of
Intelligent Systems Technologies and Applications, International Journal of
Modelling Identification and Control (EI indexed) and International Journal of
Business Intelligence and Data Mining. He is currently supervising four PhD
students and holding several government research grants. He has published over
50 research papers in peer-reviewed journals and conferences.



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