Keynote lectures

• Surya R. Kalidindi "Materials Innovation Driven by Data and Knowledge Systems"
• Federico Zipoli "Accelerated Material Discovery"

• Amber Geurts "From margins to mainstream: the emergence of data- driven materials research as field of science and business"
• Felix Göküzüm "Neuronal networks in multiscale simulations: Hands-on session"
• Frank & Holger Großmann "Materials 4.0 can only exist with blockchain solutions"
• Rebecca Janisch "Atomistic aspects of deformation and fracture"
• Marc-Andre Keip "On the use of machine learning methods in multiscale modeling"
• Benjamin Klusemann "Application of machine learning approaches in the context of processes and materials with focus on artificial neural networks"
• Thomas Lehmann "Machine Learning with Python: Hands-on Session"
• Stefanie Reese "Model reduction & data-driven mechanics - developments and applications"
• Patrick Rinke "Machine Learning in Materials Science"
• Emre Topal "Neuronal Networks for the improved reconstruction of X-ray CT Data"
• Daniel Urban "Building a materials database for the digital representation and modelling of materials along the product life cycle"
• Anja Waske "Non-destructive testing of materials and composites"
• Weihui Xie "SJTU and Zhi-hong Summer School Series"

• Omur E. Dagdeviren "Controlled Manipulation of Individual Molecules on Surfaces and Comparison with Machine Learning Approaches"
• Robert Jones "Plasmonic Nanocatalysis - Do shape and size matter?"
• Guohua Zhao "Understanding alloy compositions and strain-hardening of TWIP Ti alloys: Material informatics and dislocation-based modelling"
• Ahmad Zainul Ihsan "Data Mining of Dislocation Microstructures: Approximating Dislocation Curvature"