Machine learning, statistical pattern recognition, probabilistic planning, adaptive systems.

Mathematical theories of the mind, learning and memory in biological and artificial neural networks.

To understand memory, learning and cognition through experiments and computational models, and to apply this knowledge to create brain-like artificial intelligence and neural prosthetic devices.

Primarily concerned with analyzing data in various forms - web logs, hypertext, XML, databases, signals and images

Learning about sequential and structured data, bioinformatics, document processing, natural language processing, pattern recognition.

Digital signal processing and applications to Biomedical Engineering and Industrial Systems.

The theory and applications of neural networks and related techniques.

An inter-departmental center at King's College London coordinating research and teaching in neural networks. Part of NEuroNet.

Mechanisms of human cognition and sensory-motor learning.

Developing theory, algorithms, and software for neural network regression and classification.