Computers

Theory of computation, computation in spiking neurons.

Hybrid and Bayesian networks.

Bayesian theory and inference, error-correcting codes, machine learning.

Visual perception, machine vision, image processing.

Computational learning theory, discrete mathematics.

Machine learning, kernel methods, kernel independent component analysis and graphical models

Bayesian inference, variational methods, graphical models, nonparametric Bayes.

Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems.

Computer vision, model-based object recognition, face recognition.

Graphical models, variational methods, pattern recognition.

Decision making and planning under uncertainty, reinforcement learning, game theory and economic models.

Neural networks and nonlinear modelling for process engineering.

Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think.

Multitask learning.

Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.

Representation and learning in neural processing systems, unsupervised learning, reinforcement learning.

Bayesian inference, Markov chain Monte Carlo simulation, machine learning.

Neural networks for sensor fusion, wireless sensor networks, software modeling, multimedia assets management architectures

Reinforcement learning, machine learning, supervised learning.

Bayesian perception, computer vision, image processing.

Learning of probabilistic models, applications to computational biology.

Research focusing on Machine Learning, Neural Networks, Kernel Machines, Computer Vision and Speech Processing.

Neural network ensembles, adaptive systems and applications in neuroinformatics.

Learning and generalization in neural networks.

Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.

Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning, causal inference, knowledge representation, preference reasoning.

Automated Analysis of ECG.

Graphical models, variational methods, machine learning, reasoning under uncertainty.

Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.

Probabilistic models for complex uncertain domains.

Handwritten recognition, convolutional networks, image compression. Noted for LeNet.

Computer vision, computational olfaction.

Machine learning, text and information retrieval and extraction, reinforcement learning.

Graphical models, learning in high dimensions, tree networks.

Machine learning, computer vision, Bayesian methods.

Gesture recognition, Gaussian Process priors, control systems, probabilistic intelligent interfaces.

Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression.

Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis.

Visual coding, statistics of images, independent components analysis.

Learning distributed representation of concepts from relational data.

Neural networks, machine learning, acoustic source separation and localisation, independent component analysis, brain imaging.

Models of human and computer vision.

Machine learning and medical data analysis, independent component analysis and information theory.

Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data analysis/industrial automation/information retrieval. Teaching activities.

Speech processing, auditory scene analysis, machine learning.

Many aspects of probabilistic modelling, identity uncertainty, expressive probability models.

Neural networks, fuzzy systems, computational intelligence.

Machine learning, pattern recognition, neural networks, voice processing, auditory computation.

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

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