Center for Scientific Computation and Mathematical Modeling Center for Scientific Computation and Mathematical Modeling

 Research Activities > Programs > Nonlinear Dynamics of Networks

Nonlinear Dynamics of Networks

 5-9 April, 2010

CSIC Building (#406), Seminar Room 4122.


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Michelle Girvan Department of Physics, IREAP & IPST, UMd
Ed Ott Departments of Physics and ECE & IREAP, UMd
Raj Roy Department of Physics IREAP & IPST, UMd
Eitan Tadmor Department of Mathematics, IPST & CSCAMM, UMd



REGISTRATION IS CLOSED. Participants were requested to pre-register and confirmation of approved applicants were emailed on or before February 16st. Confirmed participants can access their record at here.
Due to the large number of applications, we regret that RSVP is now closed to new applicants.


The interconnection of many dynamical units to form a complex system can lead to unexpected collective behavior. This dynamics depends upon both the individual characteristics of the participating units, as well as the topological character and properties of the network of their connections. This workshop will focus on gaining understanding of general principles and techniques of analysis that will be of broad use in the many applications where networked system dynamics is a significant issue. Another aim of the workshop will be to highlight particularly important examples of applications where the issue of network dynamics arises.

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Understanding the dynamics of networked systems is becoming an increasingly important and essential component in many areas of science and technology. Examples include social networks, communication and computer networks, gene networks, networks of neurons, etc. Dynamics on such networks include such problems as synchronization of temporal behavior of units composing a network, robustness of function to network damage (either intended or unintended), etc. The dynamics of networks themselves (i.e., change of network topological structure with time) is also an essential issue in many cases. Examples of issues in this area include adaptive evolution of network topology, formation and growth of networks, etc.

It is intended that all of the above, as well as related issues, will be open for discussion at this workshop. The two overarching goals of the workshop will be

  • To contribute to the understanding of common, basic principles of network dynamics, and
  • To uncover useful general analysis techniques for the study of these systems

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Name Affiliation
Albert-Laszlo Barabasi Northeastern University
John Baras University of Maryland
Ernest Barreto George Mason University
Erik Bollt Clarkson University
Damon Centola M.I.T. Sloan School
Aaron Clauset Santa Fe Institute
Reuven Cohen Bar-Ilan University
Iain Couzin Princeton University
Jim Crutchfield University of California, Davis
Raissa D'Souza University of California, Davis
Dan Gauthier Duke University
Michelle Girvan University of Maryland
Kimberley Glass University of Maryland
Carl Kingsford University of Maryland
Perinkulam Krishnaprasad University of Maryland
Jurgen Kurths University of Potsdam
Daniel Larremore University of Colorado at Boulder
David Liben-Nowell Carleton College
Yang Liu Northeastern University
Sebastien Motsch University of Maryland
Adilson Motter Northwestern University
Edward Ott University of Maryland
Louis Pecora U.S. Naval Research Laboratory
Dietmar Plenz National Institute of Mental Health
Mason Porter University of Oxford
Indika Rajapakse Fred Hutchinson Cancer Research Center
Sidney Redner Boston University
Juan Restrepo University of Colorado at Boulder
Michael Rosenblum University of Potsdam
Rajarshi Roy University of Maryland
Paul So George Mason University
V.S. Subrahmanian University of Maryland
Eitan Tadmor University of Maryland
Dane Taylor University of Colorado
Alessandro Vespignani Indiana University
Ralph Wachter Office of Naval Research


A limited amount of funding for participants at all levels is available, especially for researchers in the early stages of their career who want to attend the full program.

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CSCAMM Visitor Guide:


Center for Scientific Computation And Mathematical Modeling (CSCAMM)
Computer Science Instructional Center (Building #406)
University of Maryland, College Park
College Park, MD 20742-3289




Poster is available here.



Partial funding is provided by the Institute for Physical Science & Technology (IPST)
and by the UMD MURI on Exploiting Nonlinear Dynamics for Novel Sensor Networks.

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CSCAMM is part of the
College of Computer, Mathematical & Natural Sciences (CMNS)