Direct numerical simulation has become one of few available means for the systematic study of physical or artificial processes for which experiments are expensive and/or time-consuming to perform. But without the aid of systematic strategies for reducing model complexity, the burdens of complex geometries, multi-physics, and operating environments coupled with an ever increasing appetite for accuracy and model fidelity, would likely render simulation an ineffective tool. Model reduction seeks to replace large-scale or infinite-order dynamical systems arising from PDE models with systems of relatively low dimension having similar response characteristics. The goal is to dissipate the fierce computational intensity that the original dynamical system may have required while still maintaining model fidelity. In the first part of this talk we will give an overview of projection methods for model reduction. The second part will consist of a short course on the fundamentals of model reduction, suitable for graduate students and researchers.

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Thanos Antoulas was born in Athens, Greece. He studied at the ETH Zurich, where he obtained his Ph.D. degree in Mathematics in 1980. Since 1982 he has been with the Department of Electrical and Computer Engineering, Rice University, where he is currently a Professor. Professor Antoulas was elected Fellow of the IEEE (Institute of Electrical and Electronics Engineers) in 1991, and has served on the Editorial Board of many journals. For the past 14 years he has been Editor-in-Chief of the journal Systems and Control Letters. His research interests are in the broad area of dynamical systems and computation including model reduction of large-scale systems. He is the author of the book "Approximation of large-scale systems", published by SIAM in 2005, and reprinted in 2008.

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