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Kevin Carlberg

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Kevin Carlberg

Principal Member of Technical Staff
Extreme-scale Data Science and Analytics Department
Sandia National Laboratories – Livermore, CA


My research combines computational mechanics, machine learning, numerical linear algebra, and high-performance computing. The objective is to discover structure in data to drastically reduce the cost of simulating nonlinear dynamical systems at extreme scale. This enables high-fidelity models to be used for many-query applications such as design optimization and uncertainty quantification.

In 2011, I received my PhD in Aeronautics and Astronautics (with a PhD minor in ICME) from Stanford University, where Charbel Farhat was my research adviser. From 2011 to 2014, I was the President Harry S. Truman Fellow at Sandia National Laboratories in Livermore, CA. Since 2014, I have been a Principal Member of Technical Staff at Sandia.

Recent publication highlights

Our preprint on structure-preserving model reduction for marginally stable LTI systems via symplectic projection is now available on the arXiv. (Joint work with L. Peng)

Our preprint on space–time nonlinear model reduction with least-squares Petrov–Galerkin projection is now available on the arXiv. (Joint work with Y. Choi)

Our preprint on using time-evolution data to enable efficient time-parallel numerical simulations is now available on the arXiv. (Joint work with L. Brencher, B. Haasdonk, A. Barth)

Our paper on analyzing least-squares Petrov–Galerkin projection in nonlinear model reduction has been published in the Journal of Computational Physics. (Joint work with H. Antil, M. Barone)


I will be giving a talk at the Department of Mathematics Smith Colloquium at the University of Kansas, May 4, 2017.

I will be giving the keynote lecture at the U2 can UQ showcase at University of Arizona, April 28, 2017.

I gave a talk at the USACM Workshop on Uncertainty Quantification and Data-Driven Modeling in Austin, TX, March 23–24, 2017. (slides)

I attended the 2017 SIAM Conference on Computational Science and Engineering in Atlanta, GA as a minisymposium organizer, speaker, and poster presenter, February 27 to March 3, 2017. (talk slides)

I gave a talk at the Workshop on Data-Driven Methods for Reduced-Order Modeling and Stochastic Partial Differential Equations at BIRS, Banff, Canada, January 29 to February 3, 2017.

Our research group celebrated the end of the 2016 ROM/UQ summer internship program with a math potluck. Thanks to Kookjin Lee, Sofia Guzzetti, Jiahua Jiang, Wayne Uy, Cagan Ozen, and Zhe Bai for a great summer!

Current funded projects

Research interests