Active Projects:

  • Downscaling and stochastic parametrization.
  • Highly extensible parallel data assimilation software package.
  • A new optimal experimental design (ODE) framework for covariance inflation and localization for ensemble filters.
  • Goal-Oriented Optimal Experimental Design for large-scale non-linear inverse problems.
  • Nonlinear/non-Gaussian data assimilation in imperfect-model settings.

Previous Research:

  • Goal-Oriented Optimal Experimental Design for large-scale linear inverse problems.
  • DATeS: OOP-based extensible data assimilation testing suite.
  • Cluster sampling filters: fully non-Gaussian filtering methodology with GMM approximation of the prior.
  • Reduced-Order sampling: solving the non-Gaussian data assimilation problem in a reduced-order-model subspace.
  • HMC sampling smoother: a Hybrid Monte-Carlo sampling smoother as alternative to 4DVAR
  • HMC sampling filter: a new Hybrid Monte-Carlo Sampling algorithm as alternative to EnKF

Other Projects:

  • Automate parameter tuning of the Hybrid Monte-Carlo filter and smoother via optimization.