WG4: Machine Learning
Scope and Objectives of WG4 on Machine Learning
Scope:
WG4 aims to integrate machine learning into nanomechanical testing and nanocharacterization to increase data analysis efficiency, improve accuracy, and reveal new insights in materials science.
Objectives:
- Promote Machine Learning Adoption:
Provide training, tutorials, and hands-on resources to help researchers apply machine learning techniques in their work. - Enhance Nanocharacterization Efficiency:
Apply machine learning to optimize data extraction and interpretation in nanocharacterization, making the process faster and more accurate. - Advance Nanomechanical Testing:
Use machine learning to predict material properties and behaviors based on nanomechanical data, improving experimental outcomes and analysis depth.
Tasks:
Task 4.1 Disseminate mainstream machine learning techniques in the community (milestone 4)
Task 4.2 Identify applications of ML with high efficiency gains for nanocharacterization
Task 4.3 Identify applications of ML with high efficiency gains for nanomechanical testing.
Upcoming WG4 Events :
2nd MecaNano Workshop on Machine Learning for Micro- and Nano-Mechanics
The 2nd MecaNano Workshop on Machine Learning for Micro- and Nano-Mechanics will take place on September 4–5, 2025, at ELTE Eötvös Loránd University, Faculty of Science, Budapest. Following the success of the first edition, this workshop continues to explore the integration of machine learning techniques in small-scale mechanical testing and materials science, with a focus ... Read more
Budapest, 1117
New Machine Learning & AI Tutorials Available!
We are excited to announce a series of tutorials focused on Machine Learning & AI applications in materials science, led by Prof. Stefan Sandfeld. These tutorials provide practical insights and hands-on examples designed for materials scientists.
Access the tutorials here (only logged-in users: link to internal page)
Dr. Edoardo Rossi
Department of Civil, Computer Science and Aeronautical Technologies Engineering
Roma Tre University
Via della Vasca Navale 79
Rome 00146, Italy
email: edoardo.rossi@uniroma3.it
Prof. Dr. Stefan Sandfeld
Director of the Institute for Advanced Simulation
Materials Data Science and Informatics (IAS-9)
Forschungszentrum Jülich GmbH
Wilhelm-Johnen-Straße
52428 Jülich
Dr. Flavio Abreu Araujo
Louvain School of Engineering
Institute of Condensed Matter and Nanosciences
Bio and soft matter
Croix du Sud 1/L7.04.02
1348 Louvain-la-Neuve
Past WG4 Events :
2nd MecaNano Workshop on Machine Learning for Micro- and Nano-Mechanics
The 2nd MecaNano Workshop on Machine Learning for Micro- and Nano-Mechanics will take place on September 4–5, 2025, at ELTE Eötvös Loránd University, Faculty of Science, Budapest. Following the success of the first edition, this workshop continues to explore the integration of machine learning techniques in small-scale mechanical testing and materials science, with a focus ... Read more
Budapest, 1117