Artificial intelligence (AI) is revolutionizing Materials Science and Engineering by introducing new approaches to the analysis, prediction and development of materials. AI MSE 2025 provides an interdisciplinary where experts from the fields of microsystems engineering, AI, computer science, robotics and smart manufacturing share and discuss their research and practical applications in the field of intelligent material integration.
 
Focus of the Conference 

• Microstructure characterization and reconstruction (image-based methods)
  Image-based methods for microstructure analysis and reconstruction enable the evaluation and optimization of material properties. 3D structures can be derived from 2D images, leading to a deeper understanding and targeted improvement of materials. 
• Prediction of material properties/microstructures
  AI technologies are used to predict material properties based on their microstructure. These innovative approaches significantly accelerate materials development. The focus is on the use of machine learning in atomistic simulations and its application to continuum-based simulation models. 
• Material discovery
  AI not only accelerates the discovery process of new materials, but also facilitates the targeted development of materials with desired properties. Adaptive learning methods in materials discovery allow AI to autonomously identify relevant information and suggest prioritized experiments. These approaches are particularly useful when physical experiments are costly or difficult to perform, as AI-driven simulations can significantly shorten experimental cycles. 
• Emerging technologies
  This section focuses on emerging technologies in Materials Science that are currently underutilized but hold great potential for the future. These include neurosymbolic methods, which combine neural pattern recognition with logic-based systems to enable complex and interpretable AI decisions; Natural Language Processing (NLP), which helps computers understand and process human language, essential for applications such as voice assistants and translation systems; Physically-informed Neural Networks (PINNs), which integrate physical laws into neural networks to provide more accurate predictions in engineering; and Neural ODEs (Neural Ordinary Differential Equations), which extend neural networks to model continuous and dynamic processes, realistically simulating time-dependent systems. 

In addition to these topics, you will have the opportunity to learn more about the future of materials science with AI. 

Share Your knowledge
The conference offers not only experienced scientists but also young researchers the opportunity to present their latest research results at AI MSE. You are invited to submit your abstracts for oral, poster and poster pitch presentations on the conference topics by 10 January 2025.  
 
Program Committee
The program committee of the AI MSE conference brings together leading scientists in AI and Materials Science. Their combined expertise and cutting-edge research ensure an outstanding scientific program that bridges the gap these two disciplines.  
The program committee will be chaired by Prof. Dr. Markus Stricker from Ruhr University Bochum, supported by his deputy Prof. Dr. Alexander Hartmaier and numerous scientists on the program advisory board.  
 

We look forward to an inspiring conference full of exciting developments and new insights. Take the opportunity to exchange ideas with experts, advance your research and expand your network!