Speaker
Description
This presentation describes the IntelliAQ project and its main achievements. The ERC Advanced grant IntelliAQ has been one of the first initiatives to explore the rapidly developing advanced deep learning concepts in the realm of air pollution research. IntelliAQ defined three core targets for which deep learning solutions should be developed: spatiotemporal interpolation, forecasting, and data quality control. Until now the project has mainly focused on the first two objectives and on tropospheric ozone as key air pollutant. We expect, however, to broaden the scope during the remaining time of the project.
Besides the scientific development of deep learning applications, the project has also contributed to building scalable and reproducible machine learning workflows and it has allowed for the development of a modern, FAIR and open data infrastructure for global air pollution data.
