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Please contact our research group leader, Andy Tyrrell, for more informaton.

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Intelligent Systems Research Group

Welcome to the Intelligent Systems Research group. Our research is inspired from linking engineering and technology with Nature and focuses on the interactions between electronic, computational & robotic systems and biological systems. Our intellectual focus is maintained through the development of novel biologically-inspired electronic, computational & robotic systems and programs inspired by Nature, the characterisation and understanding of biological and biomedical signals and the exploitation of evolutionary mechanisms in system design and optimisation. We are interested in creating and conducting research into novel systems and architectures endowed with capabilities such as adaptation, evolution, growth, healing, replication, and learning. These technical developments are applied to a variety of real-world applications areas. These include: VLSI technology design and fabrication, autonomous intelligent vehicles, fault-tolerant systems, control systems, neural & immune system modeling and analysis of medical data for healthcare.

Collective Adaptive Systems : Theory and Design

Collective adaptive systems consist of many autonomous units that interact in a variety of ways over multiple scales. We focus our work primarily on swarm robotic systems, developing novel approaches to self-healing systems: endowing collectives with the ability to detect, diagnose and repair failures for themselves. We draw heavily from the field of Artificial Immune Systems (AIS): techniques inspired by the workings of the immune system and also multi-agent systems. We make use of a variety of robotic platforms, from ground-based, to aerial to underwater robots and have work within a state of the art purpose built robotics laboratory.

Evolvable and Developmental Hardware

Evolvable hardware offers much for the future of complex system design. Evolutionary techniques not only give the potential to explore larger solution spaces, but when implemented on hardware allow system designs to adapt to changes in the environment, including failures in system components. Our work spans several areas, including the design of fault-tolerant hardware, evolvable array-based architectures, custom ASIC solutions for intrinsic evolvable hardware, the use of computational development within evolvable hardware, and automatic design of next generation nano-CMOS systems.

Evolutionary Computation

The group carries out a variety of research in the field of evolutionary computing from theory to practice. Particular areas of focus for the group in this area are in Cartesian Genetic Programming, artificial biochemical networks and multi-agent system. Within these areas we concentrate on the methods and the design of evolvable, scalable, biologically-motivated representations. This includes work upon developmental representations, implicit context representations, and multiple chromosome approaches. In addition to our theoretical work, we also have experience of applying evolutionary computation to a variety of real world problems, including robotic control, biological sequence understanding, medical classification, and image processing.

Diagnostic and Assistive Healthcare Technologies

Work in this area focuses upon the application of evolutionary algorithms, signal processing and computer vision methods to problems in medical diagnosis and assistive technologies. We have successfully applied these methods to a number of healthcare problems, including the diagnosis and monitoring of neurological conditions (such as Parkinson's disease and Alzheimer's disease), the automated interpretation of mammograms, and the development of technologies for the rehabilitation of patients.

Computational Neuroscience and Immunology

Computational neuroscience uses mathematical analysis and modeling to advance our understanding of information processing in the human brain. Statistical signal processing methods, including Fourier, wavelet and Kalman filter based optimal spectral tracking techniques, have been developed and applied to brain signals. Modeling studies supplement this work, using detailed biophysical and phenomenological models. Application areas include neuroimaging, clinical studies and control of voluntary movements. Computational immunology is the application of computational modeling and simulation to address issues within experimental immunology. Our work focuses on the development of agent-based simulations of immune system function and we collaborate extensively with experimental immunologists at York and further afield in the USA, and have developed simulations for autoimmune diseases and early formation of immune organ function. We make use of extensive statistical analysis of our simulations, in an effort to increase confidence in the usefulness of the results when interpreted into an immunological context.

Microelectronics Design

Our research in this area covers a number of aspects of microelectronics design, including research into VLSI silicon based design of novel hardware architectures (e.g. novel FPGA designs), biologically inspired architectures and computation models for adaptable and fault-tolerant designs. It includes the development of design tools and/or technologies, including synthesis, simulation and optimisation of reconfigurable hardware. Our work also involves the design of many-core architectures and software environments based around such architectures.

We invite potential postgraduate students who are interested in a research degree in one or more of our research areas to explore our web-pages, and the list of research projects. If you come across a topic that excites you and you are interested in working with us, please contact the leader of our research group Andy Tyrrell. We are also keen on collaborative research with industry and academic groups who share common interests in state-of-the-art research in one of our areas.

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