Short-term memory, learning and memory in the brain, computational learning theory.

Neurally controlled robotics.

Computational learning, complex probability modelling.

Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks.

Reinforcement learning.

Brain Computer Interface.

Learning and inference in complex probabilistic models.

Varied machine learning and data analysis topics, including Bayesian inference, relevance vector machine, probabilistic principal component analysis and visualisation methods.

Machine learning; applications to human-computer interaction, vision, neurophysiology, biology and cognitive science.

Neural networks applied to visual perception and computational modeling of mental disorders.