Artificial Intelligence
Significant advancements in science and society are increasingly driven by the application of AI methodologies, which are most effective when substantial datasets are used. MaX is committed to ensuring that AI-driven analyses are grounded in reliable, reproducible data, supporting robust and accurate outcomes in materials research and applications.
Artificial Intelligence (AI) allows for more efficient analysis of complex data sets, enabling researchers to predict material properties, behaviors, and performance more accurately. This integration can significantly reduce the time and cost involved in experimenting with new materials, as AI can identify promising candidates more quickly than traditional methods. Additionally, machine learning (ML) models can uncover patterns and insights from large-scale datasets that might be difficult or impossible for humans to detect.
MaX is increasingly active in the field of AI. Our growing engagement to work at the intersection of AI and materials science and engineering reflects our commitment to leveraging AI methods for materials discovery and design. Examples of our involvement are our sponsorship and participation in two major conferences:
Artificial Intelligence for Advanced Materials (AI4AM2025)
Date: 08-10 April 2025
Venue: San Sebastián, Spain
MaX was proud to be a Silver Sponsor of the conference, an international event dedicated to AI applications in advanced materials research.
At our booth, we displayed recent developments from our partners, highlighting how AI and HPC enhance materials design. Topics included machine learning for interatomic potentials, automated simulations, and AI-driven workflows. In addition, MaX partners Elisa Molinari (CNR-Nano), Nicola Marzari (UBREMEN), and Cristiano Malica (UBREMEN) presented key scientific work across multiple sessions.
Artificial Intelligence for Advanced Materials (AI4AM2024)
Date: 02-04 July, 2024
Venue: Barcelona, Spain
MaX was honored to be among the sponsors of the conference, an international event dedicated to AI applications in advanced materials research.
The event was a valuable opportunity to engage with leading experts from research and industry and discuss topics such as predictive modeling, quantum computing, and big data analytics. Thanks to this event, MaX strengthened collaborations and ensured alignment with technological advancements in computational materials science.