Zhou Jing

In order to further promote the internationalization of the School and actively promote scientific research cooperation with research groups overseas, by the invitation of the School of Mathematics, Physics and Statistics, Professor Lin Haixiang from Delft University of Technology in the Netherlands made a speech entitled "Integration of the Data Assimilation and Machine Learning as Constraints" for teachers and students on June 22^nd.

Prof. Lin Haixiang began by exploring the potential of data assimilation and machine learning in solving complex environmental problems, especially how to improve the accuracy of air quality forecasting through the integration of the two. Then, Prof. Lin outlined the basic principles and advantages of data assimilationand machine learning, pointing out that data assimilation is a model-based approach that can effectively use observational data to reduce uncertainty inmodel predictions. Finally, Prof.Lin shared a practical case of combining data assimilation and machine learning technology - the improvement of air quality monitoring and forecasting. This case study not only shows the remarkable effect of the combination of the two methods in improving the forecast accuracy, but also reveals the broad prospect of the synergistic effect of data assimilation and machine learning. Through this lecture, participants gained a deeper understanding of the application of data assimilation and machine learning to constrained optimization problems, which stimulated their interest in future interdisciplinary research.