Theory and algorithms    

  • Learning from data streams, non-stationary data, spatiotemporal data
  • Active, semi-supervised, and unsupervised learning 
  • Embeddings, sparsity, and high-dimensionality
  • Privacy-preserving machine learning

Applications

  • Climate science: Climate Informatics
  • Sustainability: energy, environment, agriculture
  • Finance