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Schedule

Monday 30 June

09:15--09:55 Andy Majda (NYU) Data Driven Methods for Complex Turbulent Systems
10:00--10:40 Marc Bocquet (CEREA) Parameter Estimation with the Iterative Ensemble Kalman Smoother and Application to a Coupled Meteorological/Tracer Low-order Model
10:45--11:25 Tea/Coffee in the Mathematics Common Room
11:30--12:10 Michal Branicki (Edinburgh) Quantifying Bayesian Filter Performance Through Information Theory
12:15--14:40 Lunch in the Mathematics Common Room
14:45--15:25 Mike Fisher (ECMWF) Time-parallel algorithms for Variational Data Assimilation
15:30--16:10 Tea/Coffee in the Mathematics Common Room
16:15--16:55 Ian Grooms (NYU) Multiscale Filtering with Superparameterization

Tuesday 1 July

09:15--09:55 Ibrahim Hoteit (KAUST) Targeted Sampling for Gaussian-Mixture Filtering High Dimensional Systems with Small Ensembles
10:00--10:40 Kayo Ide (UMD) Coping with Multi-scale in Ensemble Data Assimilation
10:45--11:25 Tea/Coffee in the Mathematics Common Room
11:30--12:10 Kody Law (KAUST) A Deterministic Approach to Filtering and EnKF for Continuous Stochastic Processes Observed at Discrete Times
12:15--14:40 Lunch in the Mathematics Common Room
14:45--15:25 Maelle Nodet (INRIA) Accounting for Correlated Observation Errors in Image Data Assimilation
15:30--16:10 Tea/Coffee in the Mathematics Common Room
16:15--16:55 Sebastian Reich (Potsdam) Particle Filter for High-dimensional Problems: Combining Optimal Transportation with Localisation

Wednesday 2nd July

09:15--09:55 Daniel Sanz-Alonso & Abhishek Shukla (Warwick) Controlling Unpredictability with Partial Observations
10:00--10:40 Peter Jan Van Leeuwen (Reading) Non-degenerate particle filters for high-dimensional systems
10:45--11:25 Tea/Coffee in the Mathematics Common Room
11:30--12:10 Andy Majda (NYU) Algorithms for Multiscale Filtering of Complex Turbulent Systems
12:15--14:40 Lunch in the Mathematics Common Room