Tomorrow’s technology

Establishing the scientific principles behind the technologies of the future, in order to transform work, health, defence and creativity.

How do we reduce toil, improve health, boost security and enhance creativity? The technologies that address these fundamental human needs always rely on scientific principles, and we develop the theories behind the technologies of tomorrow.

The greatest labour-saving innovation today is efficient computation. We work on theoretical aspects of alternatives to electronic computing, such as memristors and photonic and quantum computing. We seek a deeper foundation for artificial neural computation, which currently resembles engineering more than science.

Can a deeper understanding of how life processes information set the stage for a biological analogue of the silicon revolution? We study whether aging is the result of a programme, rather than an entropic necessity. If so, how can we slow it? We develop new mathematics for high dimensional inference and apply it to precision medicine.

Working with the US Department of Defense and the Ministry of Defence, we lay the theoretical groundwork for moonshot technologies of national interest. These range from self-similar materials, to sensor dust, to repairable instead of robust, to harvesting energy from fluctuations in the environment.

In our theme on the theory of human enterprise, we investigate how we can surpass the limitations of the individual through collective creativity.

  • Machine learning the regulatory structure of cell states

    Learning the cell-state space

    Building machine learning models that mimic the behaviour of cells in silico to improve the prediction of genes for cell programming.

  • Informative experiment design

    Developing the mathematical structure of experiments using information theory and combinatorics to speed up the discovery of new cell types.

  • Fractal structures

    Using fractal, or self-similar, patterns to design the lightest possible load-bearing structures with new strength-to-mass scaling laws.

  • Information thermodynamics

    Understanding the physical nature of information and how it relates to energy transfer and new technologies that make use of these insights.

  • Puzzles in packing

    Predicting the geometry and behaviour of densely packed objects from first principles, from spheres to polydisperse spheres to cells.

  • Remembering to learn

    Understanding the dynamics of networks of memristors, a new paradigm for low-power computation inspired by the structure of the brain.