Research projects in the Artificial Intelligence Group
The group undertakes a wide number of projects, often in collaboration with other groups at UWE. A list of our previous projects is also available. Recent or current projects include:
Intelligent Statistical Disclosure Control
A long term collaboration with the UK Office of National Statistics applying meta-heuristics to the problem of how to protect confidentiality in publicly available datasets (e.g. employment statistics, industrial outputs) while maximising the usefulness of what is published. Led by Smith and Clark, with Serpell.
EU FP7: 2010-2013
A collaboration with five companies and two other Universities to create adaptive robotic platforms to aid independent living in older adults. Led by Caleb-Solly, with Bristol Robotics Lab.
Biologically inspired transportation: a distributed intelligent conveyor
Creation of a cilia-inspired smart surface and evolutionary design of appropriate controllers. Bull, project led by Adamtzky Unconventional Computing Group, in collaboration with Manchester.
Applications of AI to create more realistic flight simulation exercises
Micro-electronics iNet project by Smith with Micro Nav Ltd evaluating the potential impact of AI for planning and speech recognition in Simulation Environments for Pilot and Air Traffic Control training.
How can I help you: Evaluation of Natural Language Interfaces to Faculty Information Systems
Higher Education Academy: 2012-13
Creation of Interactive AI based methods for accessing student information systems by Smith.
Industrial Extensions to Production Planning and Scheduling (PPExt)
EU FP7, 2010-2013
Development of improved techniques to help industries improve efficiency in areas such as lot sizing and scheduling, cutting and packing. Marie Curie International Research Staff Exchange Scheme with four partner Universities from Portugal and Brazil led by Clark, with Smith.
Learning and Computation in Disordered Networks of Memristors: Theory and Experiments
Creation and use through evolutionary design of memristors. Bull, led by Adamatzky, Unconventional Computing Group
The evolutionary design of chemical neural networks. Bull, led by Adamatzky (PI) Unconventional Computing Group, in collaboration with the Universities of Cardinal Stefan Wyszynski, Friedrich Schiller in Jena, and Southampton.
HEAT@UWE: Bridging the gaps in Health, Environment And Technology
Initiative to form new multi-disciplined research themes across UWE. Bull, led by Williams, Centre for Sustainable Planning and Environments.