[What is CoCo?] [What Are Complex Systems?]
[CoCo Seminar Series] [Research Foci] [Projects] [Contact Us]
- Spring 2015 CoCo seminar schedule now available!!
- Advanced Graduate Certificate Program in Complex Systems Science and Engineering is accepting new students
CoCo is a campus-wide interdisciplinary research group at Binghamton University that studies the collective dynamics of various types of interacting agents as complex systems. Its goals are to
advance our understanding about the collective dynamics of physical, biological, social, and engineered complex systems through scientific research,
promote interdisciplinary collaboration among faculty and students in different schools and departments, and
translate the understanding to products and processes which will improve the well-being of people at regional, state, national and global scales.
With the active participation of faculty members with diverse backgrounds, CoCo has been playing a key role in producing several new interdisciplinary research projects since 2007.
There is a mailing list run by the CoCo group for general discussions on complex systems. To subscribe, please contact Hiroki Sayama.
List of Faculty Participants
See news article on CoCo in the 2009 Binghamton University Research Magazine
Complex systems are networks of many components with nonlinear interactions which arise and evolve through self-organization, such that the system is neither completely regular nor completely random, permitting the development of emergent behavior. These properties can be found in many real-world systems, e.g., gene regulatory networks in a cell, physiological systems, brains and other neural systems, food webs, stock markets, the Internet, and social networking systems. We study their structural/dynamical properties to obtain general, cross-disciplinary implications and applications.
Engineering Building R-3 (SSIE Conference Room)
With refreshments; followed by free discussions
February 4: Nasim Sabounchi (Systems Science and Industrial Engineering)
"System Dynamics Modeling As a Tool to Inform Health Policy" [Flyer]
February 18: Ziang (John) Zhang (Electrical and Computer Engineering)
"Distributed Energy Management Algorithms in Future Power Systems" [Flyer] [Video]
March 18: Prahalad Rao (Systems Science and Industrial Engineering)
"Graph Theoretic Approaches for Analysis of Dynamical Systems: Application to Manufacturing and Neurophysiology" [Flyer] [Video]
April 1: Sung Hoon Chung (Systems Science and Industrial Engineering)
"Computational Sustainability: A Dynamic Game Approach" [Flyer] [Video]
Fall 2014 / Spring 2014 / Fall 2013 / Spring 2013 / Fall 2012 / Spring 2012 / Fall 2011 / Spring 2011 / Fall 2010 / Spring 2010 / Fall 2009 / Spring 2009 / Fall 2008
Social Dynamics: The utilization and extension of agent-based modeling, evolutionary theory, game theory, and network theory to model, analyze and improve the behaviors of social systems. Current research topics include group decision making dynamics, multi-level analysis of organizational behavior, strategies in social interactions, and models of local community interactions, as well as their application for the improvement of the heathcare systems in local community.
Network Dynamics: The utilization and extension of complex network theory to explore the connectivity between elements, growth and self-organization, and dynamical evolution of various complex networks. Current research topics include theoretical models of coevolutionary adaptive networks and social network analysis.
Swarm Dynamics: The investigation of collective behavior and pattern formation in massive populations of biological or biomimetic autonomous agents. Current research topics include decentralized control and interactive design methods for homogeneous and heterogeneous self-propelled particle swarms and the application of particle models for ecological systems.
- Evolutionary perspective on collective decision making
- Teaching social complexity and multidisciplinary team building
- Linking youth and community through Information Technology
- Network analysis of real-world multi-dimensional social relationships
- Modeling and predicting state-topology coevolution of complex adaptive networks
- Robustness and adaptation in morphogenetic collective systems
- Self-organization of large-scale heterogeneous self-propelled particle swarms
- Developing interactive demonstrations of complex systems simulation
Hiroki Sayama, DSc, Director (Systems Science and Industrial Engineering & Biomedical Engineering)
Andreas Pape, PhD, Associate Director (Economics)
Collective Dynamics of Complex Systems Research Group
Binghamton University, State University of New York
© Copyright 2007-2015 Collective Dynamics of Complex Systems Research Group, Binghamton University