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AC.CES 2011 : Aachen Conference on Computational Engineering Science


When Jul 13, 2011 - Jul 15, 2011
Where Aachen, Germany
Submission Deadline Apr 20, 2011
Categories    optimization   inverse problems   model order reduction   computational engineering

Call For Papers

Inverse problems have emerged as an increasingly important paradigm in computational engineering science (CES). In contrast to classical problems in CES, the focus is on finding the cause for a given effect. Inverse problems are often ill-conditioned, and thus present an enormous challenge for theoretical insight and the development of suitable methods.

The Aachen Conference on Computational Engineering Science (AC.CES) will bring together leading experts in theory, method development, and applications related to inverse problems in computational engineering. The main objectives of the conference are to present cutting-edge research and to facilitate interdisciplinary collaboration. The conference will consist of a series of plenary sessions featuring invited talks by leading experts; these will be accompanied by poster sessions by regular participants.

The following speakers have confirmed their attendance at AC.CES.

* Lorenz T. Biegler (Carnegie Mellon University)
* Peter G. Binev (University of South Carolina)
* Kai-Uwe Bletzinger (TU Munich)
* Albert Cohen (Université Paris 6)
* Ronald A. DeVore (Texas A&M)
* Christodoulos A. Floudas (Princeton University)
* Omar Ghattas (University of Texas at Austin)
* Max Gunzburger (Florida State University)
* Matthias Heinkenschloss (Rice University)
* Barbara Kaltenbacher (University of Graz)
* Rudibert King (TU Berlin)
* Sandro Macchietto (Imperial College London)
* Anthony T. Patera (MIT)
* Rolf Rannacher (Heidelberg University)
* Stefan Ulbrich (TU Darmstadt)
* Karen Willcox (MIT)
* Enrique Zuazua (Basque Center for Applied Mathematics)

Among the topics discussed at the conference are:

* applications, e.g. aerodynamics, geophysics, imaging, medicine, acoustics
* data estimation and retrieval
* theory: existence, uniqueness, and stability
* regularization
* optimization and control
* PDE-constrained optimization
* model order reduction
* model identification and discovery
* model-based experimentation
* parameter identification
* software tools

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