During her secondment at Predictim Globe, Mihret Tegegn contributed to the development of predictive models for corrosion rates using machine learning techniques.

The work focused on applying data-driven approaches to improve the prediction and analysis of corrosion behaviour, supporting more accurate and efficient monitoring strategies. Through this collaboration, Mihret gained valuable experience at the intersection of materials science, corrosion engineering, and artificial intelligence.

In addition to her technical contributions, she also participated as a co-author in a research paper developed during the secondment, highlighting the collaborative and interdisciplinary nature of the work carried out within the SEA-CHEM network.