Alireza Doostan
Assistant Professor
Aerospace Engineering Sciences
University of Colorado
Boulder, CO 80309-0429
ECAE 189
doostan@colorado.edu
Arriving January 2010
Ph.D., Structural Engineering, The Johns Hopkins University, 2006
M.A., Applied Mathematics and Statistics, The Johns Hopkins University, 2006
M.S., Structural Engineering, Sharif University of Technology, 2002
B.S., Civil Engineering, Sharif University of Technology, 2000
2007-2009, Engineering Research Associate, Center for Turbulence Research, Stanford University
2007-2007, Postdoctoral Fellow, Center for Turbulence Research, Stanford University
Postdoctoral Fellowship, Center for Turbulence Research, Stanford University, 2007
Uncertainty quantification (UQ), computational stochastic mechanics, model reduction for stochastic systems, large-scale statistical inverse analysis, model verification and validation (V&V), estimation theory and data assimilation, structural dynamics
A. Doostan, G. Iaccarino, A least-squares approximation of partial differential equations with high-dimensional random inputs, Journal of Computational Physics, 228 (12), 2009, 4332-4345
P. Constantine, A. Doostan, and G. Iaccarino, A hybrid collocation/Galerkin scheme for convective heat transfer problems with stochastic boundary conditions, International Journal for Numerical Methods in Engineering, 2009, DOI: 10.1002/nme.2564
T. Chanstrasmi, A. Doostan, and G. Iaccarino, Pade-Legendre approximants for uncertainty analysis with discontinuous response surfaces, Journal of Computational Physics, 228 (19), 2009, 7159-7180
R. Ghanem, A. Doostan, and J. Red-Horse, A probabilistic construction of model validation, Computer Methods in Applied Mechanics and Engineering, 197 (29-32), 2008, 2585-2595
A. Doostan, R. Ghanem, and J. Red-Horse, Stochastic model reduction for chaos representations, Computer Methods in Applied Mechanics and Engineering, 196 (37-40), 2007, 3951-3966
R. Ghanem and A. Doostan, On the construction and analysis of stochastic models: Characterization and propagation of the errors associated with limited data, Journal of Computational Physics, 217, 2006, 63-81
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