Intelligent Systems and Nano-science Research Group

Main application areas

Explore our projects


Professor Andy Tyrrell
Head of Intelligent Systems and Nano-science Research Group

Our research links engineering and technology with nature. We focus on electronic, computational and robotic platforms and their interactions with biological systems. We also undertake fundamental research into the next generation of nanoelectronic hardware.

We develop novel biologically-inspired electronic, computational and robotic systems. We work to characterise and understand biological and biomedical signals, and exploit evolutionary mechanisms in system design and optimisation. This systems-level research is underpinned by our fundamental studies into the next generation of innovative nanoelectronic materials and devices, including bio-molecular electronic systems and spin-based electron devices.

We use our technical developments in a variety of real-world applications, including:

  • VLSI technology design and fabrication
  • autonomous intelligent vehicles
  • fault-tolerant systems
  • control systems
  • neural and immune systems
  • diagnostic technology for healthcare
  • modeling and analysis of medical data

Research capabilities

Adaptive devices and architectures

Adaptive devices and architectures offer much for the future of complex system design. 

  • Evolvable and adaptive hardware
  • Reconfigurable devices and systems
  • Bio-inspired algorithms
  • Collective and autonomous robotics

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Bio-molecular electronics

In this area we focus on the integration, detection and manipulation of biological materials using electronic devices.

  • Molecular computation
  • Sensing and diagnostics
  • Biology/electronics interfaces

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Nano-scale technologies

Our ultimate goal is to develop spintronic devices built on the nanometre scale.

  • Spintronic materials and devices
  • Nano-device fabrication and analysis
  • Self-assembling nano-structures
  • Quantum nano-electronics

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Computational biomedical systems

We study evolutionary algorithms, signal processing and computer vision methods, and apply our findings to healthcare problems.

  • Clinical decision support
  • Modelling and simulation
  • Data analytics
  • Translation

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