Mathematical Methods for the Study of Self-organization in the Biological Sciences

The actual thematic programme 'Mathematical Methods for the Study of Self-Organization in the Biological Sciences' has been postponed to the 14th November - 9th of December 2022 and will take place at the Erwin Schrödinger Institute in Vienna, Austria. As a warm-up we present a series of online talks by mathematicians and biologists on the 10-11th of December 2020.

Self-organization is pervasive in biology as living organisms are by essence systems that have self-assembled and self-organized in the course of their development. Self-organization refers to the ability of systems made of a large number of independent agents interacting through rather simple and local rules to generate large scale spatio-temporal coherent structures with typical dimensions orders of magnitude larger than those associated with each individual agent. Examples of self-organisation are natural network formation (like capillaries and leaf venation), collective dynamics (like flocking, herding and pedestrian dynamics), opinion dynamics, landscape formation, tissue and organ formation... This programme brings together mathematicians and biologists to provide a broad overview of the various self-organization mechanisms that prevail at the various scales and the mathematical models by which they can be described or even explained. 

Coming soon.

This event has no subevents associated to it.
  • Grégoire Clarté (U Paris-Dauphine)
  • Antoine Diez (Imperial College, London)
  • Angelika Manhart (University College London)
  • Sara Merino-Aceituno (U Vienna) — Organizer
  • Human Rezaei (INRAe)
At a glance
Type:
Online Workshop
When:
Dec. 10, 2020 -- Dec. 11, 2020
Where:
Erwin Schrödinger Institute - virtual
Part of:
Mathematical Methods for the Study of Self-organization in the Biological Sciences (Thematic Programme)
Organizer(s):
Pierre Degond (Imperial College, London)
Marie Doumic (Sorbonne U, Paris)
Anna Kicheva (ISTA, Klosterneuburg)
Sara Merino-Aceituno (U Vienna)
Christian Schmeiser (U Vienna)
More:
Website