Thu, 04 Nov 2021

12:00 - 13:00
L3

Active Matter and Transport in Living Cells

Mike Shelley
(Courant Institute of Mathematical Sciences)
Further Information
Mike Shelley is Lilian and George Lyttle Professor of Applied Mathematics & Professor of Mathematics, Neural Science, and Mechanical Engineering, and Co-Director of the Applied Mathematics Laboratory. He is also Director of the Center for Computational Biology, and Group Leader of Biophysical ModelingThe Flatiron Institute, Simons Foundation
Abstract

The organized movement of intracellular material is part of the functioning of cells and the development of organisms. These flows can arise from the action of molecular machines on the flexible, and often transitory, scaffoldings of the cell. Understanding phenomena in this realm has necessitated the development of new simulation tools, and of new coarse-grained mathematical models to analyze and simulate. In that context, I'll discuss how a symmetry-breaking "swirling" instability of a motor-laden cytoskeleton may be an important part of the development of an oocyte, modeling active material in the spindle, and what models of active, immersed polymers tell us about chromatin dynamics in the nucleus.

Mon, 18 Feb 2019
13:15
L1

Quasi-isometric embeddings of symmetric spaces and lattices

Thang Nguyen
(Courant Institute of Mathematical Sciences)
Abstract

Symmetric spaces and lattices are important objects to model spaces in geometry and topology. They have been studied from many different viewpoints. We will concentrate on their coarse geometry view point in this talk. I will first quickly go over some well-known results about quasi-isometry of those spaces. Then I will move to the study about quasi-isometric embeddings. While results in this direction are far less complete and well-studied, there are some rigidity phenomenons still happening here.

Fri, 20 Jun 2014

16:30 - 17:30
L1

Universality in numerical computations with random data. Case studies

Prof. Percy Deift
(Courant Institute of Mathematical Sciences)
Abstract

Universal fluctuations are shown to exist when well-known and widely used numerical algorithms are applied with random data. Similar universal behavior is shown in stochastic algorithms and algorithms that model neural computation. The question of whether universality is present in all, or nearly all, computation is raised. (Joint work with G.Menon, S.Olver and T. Trogdon.)

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