People
Board
Frans A. Oliehoek
Director ELLIS Delft
Interactive learning and decision making, reinforcement-learning, planning and causal models, multiagent learning
Robert Babuska
Advisory Board ELLIS Delft
Reinforcement learning, nonlinear control, data-driven model construction, deep learning
Jens Kober
Advisory Board ELLIS Delft
Motor Skill Learning, Reinforcement Learning, Imitation Learning, Deep Learning, Interactive Learning
Unit coördinator
Faculty
Hayley Hung
Machine Perception, Multisensor Fusion, Social Signal Processing, Affective Computing
Jan van Gemert
Computer Vision, Automatic Image and Video Recognition, Visual Inductive Learning Priors, Data efficient Deep Learning
Dariu Gavrila
Intelligent Vehicles, Machine Perception
Marcel Reinders
Machine learning, Computational biology, Knowledge-informed machine learning, Bioinformatics, Health analytics
Matthijs T.J. Spaan
Safe and robust reinforcement learning, Sequential decision making, Trustworthy AI algorithms
Sicco Verwer
Interpretable model learning, Declarative machine learning, State machines, Decision trees, Optimization.
Joana de Pinho Goncalves
Jesse Krijthe
Causal inference, Machine learning theory, Philosophy of data science, Health
Elvin Isufi
Geometric Deep Learning, Graph-Based Learning, Graph Signal Processing, Recommender Systems
Julian Kooij
Multi-sensor Perception, Machine Learning, Self-driving vehicles, Situation analysis and Prediction, Probabilistic inference, Representation learning, 3D Urban Understanding lab
Claudia Hauff
David Tax
Wendelin Böhmer
Odette Scharenborg
Inclusive speech technology, Automatic speech recognition, Bias, Fairness, Language technology
Javier Alonso-Mora
Motion Planning, Multi-robot Systems, Robot Autonomy, Intelligent Transportation, Learning for Coordination and Planning
Peyman Mohajerin Esfahani
Decision-making under uncertainty, Control and optimization, Reinforcement learning, Anomaly detection in dynamic environments
Luciano Cavalcante Siebert
Value alignment, Value estimation, Trustworthy AI, (Inverse) Reinforcement learning
Neil Yorke-Smith
Data-driven optimisation, Agent-based modelling, Reinforcement learningm social simulation
Anna Lukina
Verification, Monitoring, Safety
Guido de Croon
Bio-inspired AI for robotics, Neuromorphic sensing and processing, Small autonomous drones
Manon Kok
Charalampos Andriotis
Luca Laurenti
Safe AI, Probabilistic machine learning, Stochastic control
Kim Batselier
Green AI, Tensor networks, Kernel machines, Nonlinear system identification
Seyran Khademi
Computer vision, Deep learning, Visual place recognition, Image retrieval
Holger Caesar
Autonomous vehicles, Computer Vision, Active Learning, Sensor Fusion, Datasets
Charlotte Frenkel
Neuro-AI, Neuromorphic Computing, Spiking Neural Networks, On-Device Learning for Adaptive Edge Computing
Alumni
Wiro Niessen
