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School/Tutorial

Winter School: An introduction to kinetic models in the emergence of complex behavior in social and economic systems

Feb 18 - 21, 2013

The University of Texas at Austin
The Institute for Computational Engineering and Sciences

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ABSTRACT

These are graduate level short courses in an introductory series of lectures  on the derivation, analysis and simulations of network structures and kinetic aspects of complex systems models. Such models  appear in problems that range from traffic, flocking dynamics, supply chain networks, information exchange or  more general dynamics in networks.  One of the goals consists into looking at the derivations and dynamics of  statistical transients or flows in discrete and continuous probabilistic settings that give rise to statistical transport models.     
 

GOALS


This winter school will be held at Institute of Computational Engineering and Sciences (ICES) at the University of Texas at Austin. It will consists of four 3 hour lectures by Dieter Armbruster (ASU), Reinhard Illner (Univ of Victoria, Canada), Vladislav Panferov (CSUN), Ravi Srinivasan (UT Austin) and Bernt Wennberg (Chalmers Univ of Tech, Sweden). The program will run from Monday February 18 to 21, 2012 and precedes the Workshop “Kinetic Theory for the emergence of complex behavior in social and economic systems” to be held at the Mathematics Department in Arizona State University on February 22 to 24, 2013

Please note: If you are applying to attend the school and are a current student, please send a copy of your CV/resume and a letter from your graduate advisor stating that they are in support of your attendence at the school to Leah Adrian: leah@ices.utexas.edu.

REGISTRATION CLOSED

ORGANIZERS

NameAffiliationEmail
Dieter ArmbrusterArizona State University, School of Mathematical and Statistical Sciencesarmbruster@asu.edu
Irene M. GambaUniversity of Texas at Austin, ICESgamba@math.utexas.edu
Ravi SrinivasanThe University of Texas at Austin, Department of Mathematicsrav@math.utexas.edu

CONFIRMED PARTICIPANTS

NameAffiliation
Leah AdrianUniversity of Texas-Austin
Ankush AggarwalUT Austin
Dieter ArmbrusterArizona State University
Tan Bui-ThanhICES
Yongyong CaiPurdue University
Matias G. DelgadinoUniversity of Maryland
michele di pierrout texas at austin
Irene M. GambaUniversity of Texas at Austin
Jeff HaackThe University of Texas at Austin
Peter HelgessonChalmers University of Technology
Jingwei HuThe University of Texas at Austin
Reinhard IllnerUniversity of Victoria, Canada
Seong Jun KimThe University of Texas at Austin / ICES
Henrike KoepkeUniversity of Victoria, Canada
Yoonsang LeeUniversity of Texas at Austin
Qin LiUniversity of Wisconsin-Madison
Lei LiDuke University
Liu LiuUniversity of Wisconsin-Madison
Geoffrey McGregorUniversity of Victoria
Jose A. Morales EscalanteTU Wien (Technical University of Vienna)
Dawan MustafaChalmers University of Technology
Vladislav PanferovCalifornia State University, Northridge
Ernesto E. PrudencioThe University of Texas at Austin
Juan D. RodriguezUniversity of Texas at Austin
Jesús Rosado LinaresUniversity of California, Los Angeles
Ravi SrinivasanThe University of Texas at Austin
Yu SunUniversity of Wisconsin-Madison
Changhui TanRice University
Maja TaskovicUniversity of Pennsylvania
Andrea ThatcherArizona State University
Amanda L. TraudNorth Carolina State University
Philip VargheseThe University of Texas at Austin
Li WangUniversity of California, Los Angeles
Bernt WennbergChalmers University, Göteborg, Sweden
Cheng YuUniversity of Pittsburgh
Chenglong ZhangUniversity of Texas at Austin


FUNDING

A limited amount of travel and local lodging is available for researchers in the early stages of their career who want to attend the full program, especially for graduate students and post-doctoral fellows.

INFORMATION FOR PARTICIPANTS

Visitor Guide

The Institute for Computational Engineering and Sciences
201 E 24th Street
ICES
The University of Texas at Austin
Austin, TX

Email: leah@ices.utexas.edu

CONFERENCE POSTER

ACKNOWLEDGMENT

Funding provided by the NSF through the KI-net Grant.