AID4GREENEST researcher Dr. Christina Schenk has presented on the the advantages and disadvantages of diverse hybrid calibration and prediction approaches and how these may enhance the prediction of steel creep behaviour at the Conference on Mathematical Aspects of Materials Science (#MS24) in Pittsburgh, Pennsylvania, USA.

This conference is organised by the Society for Industrial and Applied Mathematics (SIAM).

Her presentation (see below) was titled “Calibrating Complex Material Models: A Comparative Analysis of Bayesian-Based, Optimization-Based and Neural Network-Based Approaches in the Presence of Uncertainty”.

We feel proud of the recognition of the research by Dr. Schenk at the conference and the international projection of her participation at MS24. This relates to the AID4GREENEST initiative, which aims to create environmentally friendly steel through artificial intelligence, thus enhancing sustainability in the industry.