• Svetlana Tokareva
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  • Meet Svetlana Tokareva

    Svetlana

    Dr. Svetlana Tokareva graduated from Bauman Moscow State technical University (Russia) in 2008 with a diploma in applied mathematics. She has earned her PhD from ETH Zurich (Switzerland) in 2013. The focus of the PhD thesis was on the development of novel highly accurate numerical methods for uncertainty quantification in hyperbolic conservation laws. After the graduation from ETH, Dr. Tokareva has spent one year in R&D for industry and joined ASCOMP, an ETH spin-off company working in computational fluid dymanics and software development for oil&gas sector. Following that, in September 2014, she became a postdoctoral researcher in the group of Prof. Remi Abgrall at the University of Zurich, where she was involved in several challenging research projects in the field of computational mathematics and scientific computing with applications in industry.

    In February 2018 Dr. Tokareva joined Los Alamos National Laboratory as a postdoctoral research associate in the Applied Mathematics and Plasma Physics Group (T-5), working on novel high order Lagrangian methods for multiphase and multi-material flows as well as applications of machine learning algorithms in computational fluid dynamics. In November 2019, she became a staff scientist in the T-5 group.

    Her research focuses on the development of novel highly accurate computational methods for advection-diffusion partial differential equations, and their applications in computational geosciences, plasma physics, multiscale material modeling, as well as adaptive uncertainty quantification methods and model reduction.


    Expertise

    • High-order numerical methods (Discontinuous Galerkin, finite volume, ENO/WENO, finite element, residual distribution)
    • Computational fluid dynamics
    • Lagrangian hydrodynamics
    • Multiphase flows
    • Multi-material flows
    • Uncertainty quantification methods
    • Machine learning
    • Model reduction