«Applying AI to material science» seminar
📅 February 20th, 2026
📍 Universidad Politécnica de Madrid, Madrid
On February 20th, we had the pleasure of hosting the seminar “Applying AI to Material Science”, a session dedicated to exploring how artificial intelligence is reshaping modern materials engineering.
We were honored to welcome our visiting PhD candidate Sandra Gajoch, who presented cutting-edge research at the intersection of machine learning and materials science. The seminar focused on two major research achievements that demonstrate the growing impact of AI-driven methodologies in the field.
The first highlighted the development of advanced AI models capable of automatically detecting and identifying objects within metallographic images. This work represents a significant step toward fully automated microstructure analysis, reducing manual effort while improving consistency, speed, and accuracy in materials characterization.
The second achievement introduced predictive models designed to forecast the susceptibility of cast iron to high-temperature corrosion. By leveraging data-driven approaches, these models provide valuable insights into material durability and long-term performance, supporting more informed design and engineering decisions.
Beyond presenting results, the session offered an open discussion on the challenges encountered during the research process—from data preparation and model validation to ensuring reliability in real-world applications— and possible future applications.
We would like to sincerely thank Sandra Gajoch for the presentation and all participants who contributed to the thoughtful discussion. Events like this highlight the transformative potential of AI in materials science and strengthen our shared commitment to pushing the boundaries of research.
At DIGEST, we look forward to continuing the conversation and developing new initiatives at the intersection of artificial intelligence and materials engineering.