FAIR-DI European Conference on Data Intelligence 2024

  • Hans-Joachim Bungartz, Technical University of Munich (TUM), Germany. 
    • Talk: My Own Private GPU Cluster: Greedy AI Folks and a Déjà-vu
  • Stefan Sandfeld, Forschungszentrum Jülich, Germany.
    • Talk: From the Roots of Data Science to Machine Learning of Materials’ Microstructures and Properties
  • Jacqui Cole, University of Cambridge, United Kingdom.
    • Talk: Auto-generated Materials Databases and Language Models
  • Miguel Marques, Ruhr University Bochum, Germany.
    • Talk: Machine-learning assisted discovery and characterization of materials
  • Michele Ceriotti, École Polytechnique Fédérale de Lausanne, Switzerland.
    • Talk: Machine-learning you can trust: interpretability and uncertainty quantification in chemical machine learning
  • Kevin Jablonka, Friedrich Schiller University Jena, Germany.
    • Talk: Transforming chemistry with transformers
  • William Robinson, Radboud University Nijmegen, Netherlands.
    • Talk: Accelerating formulation design by understanding the physical properties of complex molecular ensembles
  • Milica Todorović, University of Turku, Finland.
    • Talk: Active learning for data-efficient optimisation of materials and processes
  • José A. Márquez Prieto, Humboldt University, Berlin, Germany.
    • Talk: AI-ready materials science data
  • Francesca Toma, Helmholtz-Zentrum Hereon, Germany.
    • Talk: Correlative characterization and data science in functional materials
  • Nicole Jung, Karlsruher Institut für Technologie, Germany.
    • Talk: The Role of Data Intelligence in Chemistry Research Data Infrastructures

For more details on the invited talks, please check the "Timetable".