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