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Members of the Scientific Computing Group develop new and efficient numerical algorithms, techniques, and methodologies for solving scientific applications on high-performance computing systems. Our research is in a spectrum of areas of vital interest to LLNL, and we work in close collaboration with Laboratory programs and other national laboratories and universities. Areas of current interest/expertise include multi-physics and multi-scale modeling, mathematical optimization, climate modeling, subsurface flow modeling, structured adaptive mesh refinement (SAMRAI), mathematical and computational biology, computational fluid dynamics, ALE-AMR techniques, high-order discretizations, first-principles molecular dynamics, quantum Monte Carlo, plasma modeling for both ICF and magnetic fusion, nonlinear systems and solvers, verification, object-oriented software design, and algorithm performance on next-generation computing architectures.

To learn more about what we do, we invite you to look at some of the projects to which our group members contribute: Climate Modeling, Qbox: Massively-Parallel First Principles Molecular Dynamics, Linear Scaling Electronic Structure Calculations, Structured Adaptive Mesh Refinement (SAMRAI), SUNDIALS, Extreme Resilient Discretizations, the Edge Simulation Laboratory, and the Extreme Materials at Extreme Scale Co-Design Center

## Group Lead

Jeff Hittinger: hydrodynamics, computational physics, adaptive mesh refinement, verification, uncertainty quantification

## Research Staff

Robert Anderson: hydrodynamics, computational physics, adaptive mesh refinement

Milo Dorr: scientific computing, numerical analysis, parallel processing, plasma models, multigrid methods

Jean-Luc Fattebert: first-principles molecular dynamics algorithms, large scale eigenvalue problems, parallel scientific computing, phase-field modeling

David Gardner: multi-scale modeling, implicit-explicit time integration, nonlinear solvers, parallel computing

Debojyoti Ghosh: numerical methods for hyperbolic PDEs, finite-difference and finite-volume methods, implicit-explicit time integration, compressible flows, scalable algorithms

Matthieu Benoit Lecouvez: numerical and functional analysis, domain decomposition methods, ordinary, partial and algebraic differential equations, linear solvers

John Loffeld: exponential integrators, numerical analysis, parallel computing, object-oriented software design

Daniel Osei-Kuffuor: preconditioning techniques for highly indefinite linear systems

Slaven Peles: complex systems, differential-algebraic equations (DAEs), uncertainty quantification, model verification and validation, multi-scale modeling, implicit-explicit time integration, nonlinear solvers, parallel computing

Cosmin Petra: large-scale numerical optimization, stochastic programming, parallel algorithms for the optimization of complex energy systems under uncertainty.

Deepak Rajan: computational optimization and integer programming; optimization problems in scientific distributed computing

Claudio Santiago: combinatorial optimization, integer programming, conic programming, convex relaxations, and nonlinear programming

Steve Smith: object-oriented software design, adaptive mesh refinement, subsurface modeling

Liam Stanton: continuum modeling and nonlinear dynamics in materials science, electrochemistry and plasmas

Tanya Vassilevska: mathematical and computational biology

Carol Woodward: nonlinear solvers, implicit PDE methods, verification, parallel computing, flow through porous media, numerical error estimation