Collective Dynamics in Biological and Social Systems

Nov 19 - 22, 2015

Department of Mathematics, Duke University
Duke University

Duke Visitor Guide

CONFERENCE SCHEDULE

CONFERENCE LECTURES

ABSTRACT

The emergence of collective dynamics is a fascinating phenomenon which arises in different context of biological and social systems. Many such systems are modeled by transport equations such as Keller-Segel-based models for chemotactic phenomenon and Cucker-Smale model for flocking. Due to the complexity of these phenomena, transport equations might contain new mathematical difficulties (e.g non-conservative system, non-hypberbolic PDE) with many open questions for both numerical and analytical studies. Moreover, many of these systems are multiscale phenomenon (e.g. from individual cells to functional organs) leading to both microscopic and macroscopic descriptions. Kinetic equations play a key role in linking these scales.

GOALS

This workshop is a followup of the meeting held at NCSU in 2013. It aims at bringing together researchers with diverse expertise on collective dynamics in biological and social systems, from experimentalists to applied mathematicians. Our goal is to stimulate interdisciplinary discussions on new developments, with a particular focus on comparing models, experimental data and numerical studies. A second line of discussions focuses on the new mathematical challenges raised by these models, e.g. link between micro and macro descriptions, complex traffic and network optimization and pattern formation.

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

Duke Visitor Guide

Department of Mathematics, Duke University (Duke)
Science Drive, Duke University, Durham, NC 27708
Durham, NC

Email: jianfeng@math.duke.edu

CONFERENCE POSTER

ACKNOWLEDGMENT

Funding provided by the NSF through the KI-net Grant. Additional support was provided by the Department of Mathematics, Duke University