Carlos A. Pereira

PhD

I'm a Research Scientist and Environment and Climate Change Canada.

My research interests include stable, efficient high and low-order computational fluid dynamics, scalable implicit-explicit solution of partial differential equations on modern GPU/CPU architectures. Currently working at the intersection of numerical discretization of PDEs and machine learning for weather prediction.

Recent Publications
Textbooks
Articles, Theses
  • C.A. Pereira and B.C. Vermeire. Hybridized Implicit-Explicit Flux Reconstruction Methods. (In Review)
  • C.A. Pereira and B.C. Vermeire. Polynomial-adaptive hybridized flux reconstruction schemes. Journal of Computational Physics 514 (2024).
  • C.A. Pereira and B.C. Vermeire. Hybridized formulations of flux reconstruction schemes for advection-diffusion problems. Journal of Computational Physics 516 (2024).
  • C.A. Pereira. Solution-Acceleration Strategies for High-Order Unstructured Methods. PhD. Thesis. Concordia University
  • C.A. Pereira and B.C. Vermeire. Performance and Accuracy of Hybridized Flux Reconstruction Schemes. Journal of Computational Physics. (2022)
  • S. Hedayati N., C.A Pereira, and B.C. Vermeire. Optimal Runge-Kutta Stability Polynomials for Multidimensional High-Order Methods. Journal of Scientific Computing 89, 11 (2021).
  • C.A. Pereira and B.C. Vermeire. Spectral Properties of High-Order Element Types for Implicit Large Eddy Simulation. Journal of Scientific Computing, 85:48, (2020).
  • C.A. Pereira and B.C. Vermeire. Fully-Discrete Analysis of High-Order Spatial Discretizations with Optimal Explicit Runge–Kutta Methods. Journal of Scientific Computing, 83(3), pp.1-35 (2020).
  • C.A. Pereira. Analysis of High-Order Element Types for Implicit Large Eddy Simulation. Master’s thesis. Concordia University. (2019).