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 August 20–24, 2018.
• 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 July 23–27, 2018.
• 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 in Los Angeles, California, June 4–6, 2018.
• 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 April 16–19, 2018.
• 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)