Omar Ghattas
Professor, Oden Institute, Department of Mechanical Engineering
Research
Research Interests:
Professor Ghattas has general research interests in forward and inverse modeling, optimization, and uncertainty quantification of large-scale complex mechanical, geological, and biological systems. With collaborators, he received the ACM Gordon Bell Prize in 2003 (for Special Achievement) and again in 2015 (for Scalability), and was a finalist for the 2008, 2010, and 2012 Bell Prizes.
Research Labs & Affiliations:
Center for Computational Geosciences, Institute for Computational Engineering and Sciences (ICES)
Select Publications
Peng Chen, Umberto Villa, Omar Ghattas. May 15, 2019. Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty. Academic Press.
Peng Chen, Omar Ghattas. March 13, 2019. Sparse polynomial approximation for optimal control problems constrained by elliptic PDEs with lognormal random coefficients.
Peng Chen, Keyi Wu, Joshua Chen, Thomas O'Leary-Roseberry, Omar Ghattas. January 24, 2019. Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions.
A Alghamdi, MA Hesse, J Chen, O Ghattas. December 2018. Bayesian inversion of heterogeneous aquifer properties from GPS andInSAR data using poroelastic subsurface models.
Peng Chen, Umberto Villa, Omar Ghattas. December 17, 2018. Taylor approximation for PDE‐constrained optimization under uncertainty: Application to turbulent jet flow.
Awards & Honors
2015 -
ACM Gordon Bell Prize
2014 -
Best Poster Award, IEEE/ACM
2014 -
SIAM Fellow
2012 -
Joseph C. Walter Excellence Award
2012 -
CM Gordon Bell Prize Finalist
2012 -
Best Visualization Award, XSEDE Conference
2010 -
ACM Gordon Bell Prize Finalist
2009 -
Best Poster Award, SC
2008 -
ACM Gordon Bell Prize Finalist
2008 -
TeraGrid Capability Computing Challenge Award