In the DAKI-FWS project, we aim to develop an AI-based analysis platform to generate forecasts for extreme events such as pandemics. We at HPI focus on data-driven analysis and development of models using many different data sources, e.g., epidemiological, medical, sequence, demographic, contact, and mobility data for pandemic modeling and forecasting. As part of our focus, we are working on data integration, including bias detection and mitigation, development of AI models such as spatio-temporal graph neural networks for pandemic forecasting, outbreak detection, and consolidating different information sources into a comprehensive dashboard. In the long term, we aim for the quantification of uncertainty in our forecasts and expandability by integrating further data while complying with data protection regulations. In addition, we are working on the newly developed platform's business and licensing model to meet the requirements of all the different industries. 

The DAKI-FWS project combines science and industry to create an early warning system that can be adapted and used across all sectors.

For more information about the project, visit the website: https://daki-fws.de