### Evening Workshops, CMCIM 2006

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1. Monday night (3 April) workshop:

*Simulation Based Optimization*

George Biros and Eldad Haber

Simulation is a powerful tool in science and engineering for predicting
the behavior of physical systems, particularly those that are governed
by partial differential equations. Moreover, progress in algorithms and
computational hardware has been responsible for improvements in
simulation.
Using today's simulation tools it has now become practical
to consider complex design problems, where we wish to determine
parameters of large systems that maximizes a certain objective, and
inverse problems where we wish to determine parameters whose behavior
matches measured data. Examples of design problems include structural
optimization, antenna design and process optimization. Geophysical
imaging, biomedical imaging, weather data assimilations are just a few
examples of inverse problems where the physics is governed by partial
differential equations.

While these types of problems are naturally posed as optimization
problems, they offer new challenges because of their large size, inexact
derivatives (when available), and ill-posedness. Current software cannot
be used because matrices of constraint gradients cannot be factored, and
computing with null space bases can be exceedingly expensive. The goal
of this workshop is to review methods for PDE-optimization problems
and to expose researches to some open problems in the field.

###
2. Wednesday night (5 April) workshop:

*Dynamic Data Driven Liquid Flows*

Craig Douglas

This workshop will be strictly hands on. It will introduce DDDAS techniques
(see http://www.dddas.org)
including dynamic modeling, errors, sensor operation,
and the symbiotic relations between the sensors and the application.
We will simulate the level of a liquid in media that is porous in one boundary
edge only and design from scratch an algorithm to maintain it at a fixed level
on average even though the liquid is disappearing through the open boundary
using a random step function.

We will develop convergence results initially using a semi-direct method, but
some of the participants may end up with a random walk by the end of the
workshop. We will iterate on the liquid problem until we develop a fast
iterative (and convergent) algorithm that we have thoroughly tested. We will
use the data from experiments to drive the entire methodology and the
algorithms will drive how and when data is collected.

This workshop will be held in one of the local watering holes, not in the
conference center. Sensor oversight and correction will be provided at
the tables.