### About

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.

My research interests include nonlinear model reduction, machine learning, computational mechanics, high-performance computing, numerical linear algebra, uncertainty quantification, time-parallel methods, Krylov-subspace methods, structure-preserving approximations, and numerical optimization.

### Recent publication highlights

- Our preprint on
**machine-learning error models**is available on the arXiv. (Joint work with B. Freno) - Our paper on
**conservative model reduction for finite-volume models**has been published online in the Journal of Computational Physics. (Joint work with Y. Choi and S. Sargsyan) - Our paper on
**stochastic least-squares Petrov–Galerkin projection**has been accepted in the SIAM/ASA Journal on Uncertainty Quantification. (Joint work with K. Lee and H. Elman) - Our preprint on
**space–time nonlinear model reduction**with least-squares Petrov–Galerkin projection is available on the arXiv. (Joint work with Y. Choi) - Our preprint on using
**time-evolution data**to enable efficient**time-parallel**numerical simulations is available on the arXiv. (Joint work with L. Brencher, B. Haasdonk, A. Barth)

### News

- I will give a talk at the SAMSI MUMS Opening Workshop in
**Durham, North Carolina** - I will be teaching Introduction to Mathematical Optimization at the ICME Summer Workshops: Fundamentals of Data Science on August 14, 2018. (register here)
- I am excited to welcome Patrick Blonigan (formerly MIT, NASA) as research staff and Kookjin Lee (formerly University of Maryland) as a postdoctoral researcher to our research group.
- I am excited to welcome Philip Etter (Stanford) and Ricardo Baptista (MIT) as 2018 summer interns to our research group.
- I gave a minisymposium plenary talk at the 13th World Congress in Computational Mechanics in
**New York, New York** - I gave a talk at the Workshop on Research Challenges and Opportunities at the interface of Machine Learning and Uncertainty Quantification at
**The University of Southern California** - I gave a talk at the Workshop on Digital Twins and ROMs at
**The Boeing Company**in Bellevue, Washington on May 15, 2018. - I gave a talk to the UQ Lab at
**Stanford University**in Stanford, California on May 3, 2018. - I gave a talk to the Reduced Models for the Cardiovascular System at
**Emory University**in Atlanta, Georgia on April 26, 2018. - I gave a talk to the Pixar Research Group at
**Pixar Animation Studios**in Emeryville, California on April 24, 2018 (slides). - I gave a talk at the SIAM Conference on Uncertainty Quantification in
**Orange County, California** - I gave a talk and presented a poster at the Model Reduction of Parametrized Systems (MoRePaS) IV in
**Nantes, France**April 10–13, 2018. - I gave a talk at the Advanced Modeling & Simulation Seminar Series at
**NASA Ames**on March 29, 2018. (slides). Talk video accessible here. - The 2017 West Coast ROM Workshop was held at
**Lawrence Berkeley National Laboratory**on November 17, 2017. - I gave a talk at the SILO Seminar Series at
**University of Wisconsin, Madison**on October 11, 2017. - I taught
**Introduction to Mathematical Optimization**at ICME Fundamentals of Data Science Summer Workshops at**Stanford University**on August 15, 2017. (register here)