Machine Learning

Aleksandra Pizurica
Bernard De Baets
Bert De Coensel	Acoustic feature engineering Sound event detection and recognition
Chris Cornelis
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
Haosheng Huang	Geospatial AI (GeoAI)
Jan Verwaeren
Joni Dambre	Deep learning Brain inspired and neuromorphic computing
Nico Van de Weghe	Geospatial AI (GeoAI) Classification Clustering Outlier detection
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
Stijn Luca
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
Willem Waegeman
Yvan Saeys