Schedule

 Day 1 (July 11, 2022):  

13:30-14:30 – What is data assimilation?
(Prof. Alberto Carrassi – Universita di Bologna, Italy, and University of Reading, UK)

14:30-16:00 – Nudging and backward-forward approach for data assimilation
(Prof. Didier Auroux  – Université Côte d'Azur, France)

16:30-18:00 – From least squares to Kalman filter, particle filter, and beyond
(Dr. Haroldo F. de Campos Velho  – National Institute for Space Research, Brazil)

 Day 2 (July 12, 2022):

13:00-14:30 – Ensemble Kalman filter
(Dr. Takemasa Miyoshi  – RIKEN Center for Computational Science, Japan)

15:00-16:30 – Optimal interpolation and variational (3D/4D) methods
(Prof. Amos Lawless  – University of Reading, UK)

17:00-18:30 – Adjoint-free approach to 4D variational data assimilation
(Dr. Max Yaremchuk  – Naval Research Laboratory, Stennis Space Center, USA)

 Day 3 (July 13, 2022): 

13:30-15:00 – Hybrid methods: The best of ensemble Kalman filters and variational methods
(Prof. Marc Bocquet  – CEREA École des Ponts & EdF R&D, Île-de-France, France)

15:00-16:30 – On particle filters and particle flow filters and smoother: towards fully nonlinear data assimilation
(Prof. Peter Jan van Leeuwen  – Colorado State University, USA)

17:00-18:30 – Data assimilation by neural networks on ocean circulation model
(Dr. Olmo Zavala-Romero  – Florida State University, USA)

 Day 4 (July 14, 2022):

13:30-15:00 – Data assimilation on space weather models
(Prof. Ludger Scherliess – Utah State University, USA)

15:00-16:30 – Data assimilation in hydrology by neural network
(Prof. Marie-Amélie Boucher  – University of Sherbrooke, Canada; visiting scientist of the European Center for Medium Range Weather Forecasts, UK)

17:00-18:30 – WRF atmospheric model and data assimilation by neural network
(Dr. Vinicius A. Almeida – Federal University of Rio de Janeiro, Brazil)

 Day 5 (July 15, 2022):

13:00-14:30 – Data assimilation: big data and exascale computing
(Dr. Takemasa Miyoshi – RIKEN Center for Computational Science, Japan)

15:00-16:30 – Data learning: integrating data assimilation and machine learning – Applications to the COVID-19 pandemic
(Dr. Rossella Arcucci – Imperial College London, UK)

17:00-18:30 – Real-time predictive modelling machine learning and data assimilation in environmental problems
(Prof. Fangxin Fang – Imperial College London, UK)