Neural computing, data mining, evolutionary computing, ensemble networks.

Unsupervised learning, machine learning, computational models of neural processing.

Statistical methods for inference and learning.

Statistical learning, machine learning approaches to computational biology, pattern recognition and control.

Stochastic generative models for complex visual phenomena.

Face recognition, Invariances in learning and vision.

Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.

Gaussian processes, image interpretation, graphical models, pattern recognition.

Unsupervised learning, probabilistic density estimation, machine vision.

Vision, Bayesian methods, neural computation.