Kinetic Descriptions of Chemical and Biological Systems:

Models, Analysis and Numerics

Mar 23 - 25, 2017

Iowa State University
Department of Mathematics

Visitor Guide

CONFERENCE SCHEDULE

CONFERENCE LECTURES

ABSTRACT

The scope of the conference is to review latest advances in the development of mathematical modeling approaches and numerical methods for kinetic descriptions of evolution in physical, chemical, and biological systems. Such evolution and often self-organization involves an interplay between non-linear interaction or reaction of the constituent “particles” and either convective or diffusive transport. Related phenomena include: front propagation and pattern formation in reaction-diffusion systems; phase transitions or bifurcations; competitive selection; aggregation; swarming and other non-conventional quasi-hydrodynamic behavior. There are many open issues in both mathematical analysis of those models and their numerical realization.

GOALS

The aim of the conference is to provide an overview of current modeling strategies, of newly developed techniques of analysis, and of novel numerical methods to capture the complex behavior produced by the mathematical models. Some techniques used are related to classical kinetic theory and hydrodynamic treatments of fluids, and others to stochastic and non-equilibrium statistical mechanical models. The lectures aim to be accessible to graduate students, postdocs, and non-experts to familiarize them with central concepts and new directions in the field. Though the audience is expected to have a general mathematical background, knowledge of technical terminology and of recent findings is not assumed.

REGISTRATION CLOSED

ORGANIZERS

CONFIRMED PARTICIPANTS

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

Email: hliu@iastate.edu

CONFERENCE POSTER

ACKNOWLEDGMENT

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