SYNERGIZE: Synergizing Numerical Methods and Machine Learning for a new generation of computational models

The SYNERGIZE project, funded by FIS (Fondo Italiano per la Scienza), seeks to advance the emerging field of Scientific Machine Learning, in which Machine Learning techniques are harmonized with Scientific Computing methods to address pressing challenges in modeling natural, social, and industrial processes. The project focuses on the development of methods rooted in algorithms from the fields of Machine Learning and Artificial Intelligence, tailored to address the complexities of Scientific Computing problems and grounded in the principles of Numerical Analysis. The methods developed through SYNERGIZE are expected to offer approximations to solutions of differential problems extremely quickly, significantly reducing computational demands and minimizing environmental impact.