Computational methods

Wednesday, June 24, 2015 - 9:00am - 10:30am
Robert Moser (The University of Texas at Austin)
One of the most challenging and important applications of computational models of physical systems is to make predictions when no observations of the quantities being predicted are available. This is the usual situation when model results are to be used to support decisions (e.g. design or operations decisions) where predictions are needed precisely because observational data are not available when the decision must be made. Predictions, then, are essentially extrapolations of available information to the quantities and scenarios of interest.
Saturday, November 1, 2008 - 4:30pm - 5:00pm
Christian Ringhofer (Arizona State University)
This talk will discuss various issues and approaches in the numerical
simulation of carrier transport in solid state materials, relevant to
the modeling of optical generation / recombination. We will discuss
aspects of deterministic and Monte Carlo methods for the solid state
Boltzmann transport equation as well as the inclusion of quantum
effects in particle based transport simulators.
Monday, December 9, 2013 - 11:30am - 12:20pm
Xavier Pennec (Institut National de Recherche en Informatique Automatique (INRIA))
Computational anatomy is an emerging discipline at the interface of geometry, statistics, image analysis and medicine that aims at analysing and modelling the biological variability of the organs shapes at the population level. The goal is to model the mean anatomy and its normal variation among a population and to discover morphological differences between normal and pathological populations.
Saturday, September 15, 2012 - 9:00am - 9:30am
Maria Emelianenko (George Mason University)
This talk gives an overview of the computational and analytical issues
underpinning mathematical modeling of polycrystalline materials on multiple spatial and temporal scales for advancing materials design and engineering.
There is a number of challenges to be faced, including the development
Tuesday, January 15, 2008 - 11:10am - 11:40am
Yannis Kevrekidis (Princeton University)
I will present and discuss a number of computational experiments associated
with the coarse-graining of atomistic/agent-based simulations. In particular, I
will discuss coarse reverse integration, as well as the use of diffusion maps
(a manifold-learning technique) to suggest the selection of certain coarse-grained observables
(reduction coordinates) for the atomistic simulations. The illustrations will come
from molecular dynamics, Monte Carlo as well as agent-based models.
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