Bio-inspired Computational Intelligence

The progress of modern science and technology, and the development and integration of composite production networks, created highly complex systems which are difficult to optimise, model, and control using traditional engineering methods.

Biological systems display remarkably effective problem-solving strategies in difficult, dynamic, and uncertain environments. Engineering models of biological intelligence include artificial neural networks, evolutionary algorithms, and swarm intelligence. They are particularly suitable to deal with complex, ill-defined, dynamic systems which are not amenable of analytical solution.

The group has a unique expertise in this highly interdisciplinary area at the crossroads of engineering, biology, and computer science. Members of the group pioneered the creation of computational methods modelling the collective intelligence of honey bee colonies, and are actively involved in the development, characterisation, and fielding of the popular Bees Algorithm.

Our aim is to carry out internationally leading research in the application of bio-inspired computational models to a wide range of engineering problems such as motor control, control systems optimisation, mechanical design, manufacturing cell formation, machine job scheduling, robotic team coordination, etc.


Professor Duc Truong Pham

Dr. Marco Castellani