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Michal Kopera

Michal Kopera portrait

Office: MB 233-B
(208) 426-1168
michalkopera@boisestate.edu

About

Michal has earned a Ph.D. In Engineering (Scientific Computing) from the University of Warwick, UK in 2011. He then moved to the Naval Postgraduate School in Monterey, CA as a National Research Council Postgraduate Fellow. He also held a Visiting Fellow position at the Isaac Newton Institute for Mathematical Sciences in Cambridge, UK, and was an Assistant Researcher at the University of California, Santa Cruz.

Michal is interested in computational and applied mathematics, specifically numerical methods for ocean modeling, high performance scientific computing, computational fluid dynamics, adaptive mesh refinement, and scientific software development.

Computational and applied math at Boise State University

Selected products

  • Müller, A., Kopera, M. A., Marras, S., Wilcox, L. C., Isaac, T., & Giraldo, F. X. (2019). Strong scaling for numerical weather prediction at petascale with the atmospheric model NUMA. The International Journal of High Performance Computing Applications, 33(2), 411-426.
  • Bonev, B., Hesthaven, J. S., Giraldo, F. X., & Kopera, M. A. (2018). Discontinuous Galerkin scheme for the spherical shallow water equations with applications to tsunami modeling and prediction. Journal of Computational Physics, 362, 425-448.
  • Marras, S., Kopera, M. A., Constantinescu, E. M., Suckale, J., & Giraldo, F. X. (2018). A residual-based shock capturing scheme for the continuous/discontinuous spectral element solution of the 2d shallow water equations. Advances in Water Resources, 114, 45-63.
  • Kopera, M. A., & Giraldo, F. X. (2015). Mass conservation of the unified continuous and discontinuous element-based Galerkin methods on dynamically adaptive grids with application to atmospheric simulations. Journal of Computational Physics, 297, 90-103.
  • Kopera, M. A., & Giraldo, F. X. (2014). Analysis of adaptive mesh refinement for IMEX discontinuous Galerkin solutions of the compressible Euler equations with application to atmospheric simulations. Journal of Computational Physics, 275, 92-117.

Additional products

Selected courses taught

  • MATH 365 – Introduction to Computational Mathematics
  • ME 471/571 – Parallel Scientific Computing
  • MATH 265 – Intro to Programming in Mathematics