Nature Inspired Computing and Engineering

Nature presents the best example of how to solve complex problems efficiently and effectively. The main objectives of the Nature Inspired Computing and Engineering (NICE) research group are therefore to develop computational models and algorithms inspired from natural intelligence found in physical, chemical, social and biological systems, and to solve practical problems arising from various engineering fields related to health, security, energy and environment.

The NICE group adopts a bi-directional research strategy consisting of a top-down, objective-driven approach and a bottom-up problem-driven approach. The top-down approach aims to build up computational models for understanding biological and social intelligence found in nature. We are particularly interested in neural information processing in the brain and the organizing principles of neural development from the evolutionary perspective.

The bottom-up approach is concerned with developing efficient mathematical and statistical, machine learning and optimization algorithms for solving complex problems found in optimization and control, signal processing and pattern recognition, data mining and knowledge extraction, multi-criterion decision-making, and self-organization of collective systems. Real-world applications include brain-computer interfacing, medical image analysis, source localization and separation, motion tracking, threat detection, copyright protection, intelligent heat solutions, aerodynamic design optimization, and robotics.

Evolutionary Optimization

Research Funding and Collaborations

Research within the NICE group has been funded by the EPSRC, BBSRC, Leverhulme Trust, Royal Academy of Engineering, as well as industry collaborators including Waterfall Solutions Ltd, Alpha-Active Ltd, Intellas UK Ltd, HR Wallingford, Bosch Thermotechnology Ltd, Aero Optimal Ltd, Santander, Moorfields Eye Hospital, Royal Surrey County Hospital and Royal Botanic Gardens, Kew.

The group has close collaborations with other research groups within the university and with other prestigious national and international institutions such as RIKEN Brain Science Institute in Japan, and Institute of Psychiatry and Epileptology, King’s College London, UK.

Demo Videos

Leader Following

Self-organised adaptive multi-robot pattern formation

Leader Following 2: Obstacle avoidance

Evolved swimming animats

Page Owner: yj0002
Page Created: Friday 12 December 2008 15:39:03 by mf0009
Last Modified: Tuesday 16 December 2014 10:57:06 by sl0022
Expiry Date: Sunday 3 October 2010 00:00:00
Assembly date: Fri Dec 19 19:01:02 GMT 2014
Content ID: 2380
Revision: 33
Community: 1028