Artificial Intelligence in Industrial Applications

Track Chairs

Daswin De Silva, Australia; Joern Ploennigs, Ireland; Evgeny Osipov, Sweden;

Topics under this track include (but not limited to):

  • Machine Learning (ML)
    • Automated Machine Learning (AutoML)
    • Deep Learning in Industrial Applications
    • Online learning from streaming data
    • Unsupervised machine learning for industrial scenarios.
    • Machine learning on Embedded Devices on the Edge
    • Scalable machine learning
    • Machine learning for multimodal information fusion
    • Interopretability and traceable ML
    • Text, image, audio, video and social media analysis in industrial applications
  • Semantic Reasoning and Digital Twins
    • Semantic Models for Industrial Applications
    • Reasoning on IoT data
    • Combined Reasoning and Machine Learning in Digital Twins
    • Context and semantic learning for industrial domain expertise
    • Digital Thread Models
  • Human Machine Interaction
    • Intelligent human behaviour monitoring in industrial scenarios
    • Intelligent human machine interaction in industrial scenarios
    • Intelligent techniques for active perception
    • Intelligent user profiling and modelling for industrial applications
  • Optimization and Control
    • Reinforced learning in Control
    • Model-Predictive Control
    • Fuzzy-based control