Machine Learning

Aleksandra Pizurica

Bert De Coensel

  • Acoustic feature engineering
  • Sound event detection and recognition

Dick Botteldooren

Dirk Deschrijver

  • Time series

Els Lefever

  • Feature engineering
  • Supervised classification
  • Clustering
  • Deep learning

Filip De Turck

  • Fusion of semantics & machine learning
  • Adaptive anomaly detection & root cause analysis
  • Cross-context learning (transfer learning)
  • Contextual bandits (context-aware reinforcement learning)

Francis wyffels

  • Reinforcement learning
  • Brain-body optimisation
  • Learning from human demonstration

Joni Dambre

  • Deep learning
  • Brain inspired and neuromorphic computing

Nilesh Madhu

Peter Lambert

  • Feature learning for multimedia compression

Peter Veelaert

  • Geometric reasoning

Pieter Simoens

  • Neuromorphic Computing

Sofie Van Hoecke

  • ML for predictive healthcare and predictive maintenance

Steven Verstockt

  • ML in sports analytics/data science and media/cultural heritage

Tijl De Bie

  • Data fusion
  • Semi-supervised learning
  • Kernel methods

Tom Dhaene

  • Data-efficient Machine Learning (DE-ML)

Tony Belpaeme

  • Learning from demonstration
  • Social machine learning
  • Machine learning for robots

Veronique Hoste

  • Feature engineering
  • Handling skew
  • Sampling
  • Genetic algorithms

Wilfried Philips

Yvan Saeys