In the Computational Science Laboratory, we do fundamental research in numerical methods and develop novel algorithms for the adaptive solution of ordinary and partial differential equations, linear algebra, optimization, machine learning, methods to model systems with uncertainty, and more. We develop high performance software for large scale-parallel platforms. We apply our new technologies to many important fields. Examples include weather modeling and forecasting, efficient simulation of multiphysics phenomena, and sensitivity analysis for multibody dynamics. Computational platforms range from multicore workstations and accelerated architectures (e.g., GPUs) to large scale supercomputers.

#### Research Interests

- Scientific Computing
- Parallel Computing
- Mathematical Software Development
- Numerical Methods for Stiff ODE, DAE
- Conservation Laws
- Machine Learning
- Advection-Diffusion-Reaction Equations
- Sparse Linear Algebra
- Sensitivity Analysis
- Data Assimilation
- Automatic Differentiation
- Air Quality Modeling
- Computational Biology