We revel in using mathematics to understand the world and improve it. Our expanding space of research projects—in physics, mathematics, AI, life, technology, finance and beyond—reflects the interests of our scientists. They are funded by grants and donors from across the globe.

  • 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.

  • Mathematics of immortality

    Deriving the mortality equation, which governs the dynamics of an ageing population, and solving it to crack the evolutionary origin of ageing.

  • Informative experiment design

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

  • Theory of genetic computation

    Understanding genetic computation using regulatory motifs, a new kind of structural and functional building block of gene regulatory networks.

  • Learning the universe

    Using machine learning to search the vast space of 10-dimensional geometries for ones that predict the Standard Model from string theory.

  • Organising a defence

    Using both theory and experimental analyses to understand how the immune system responds to an alien invasion such as coronavirus.

  • The fate of real systems

    Improving our understanding of real-world networks with sophisticated analyses of realistic complications.

  • Hidden communities

    Employing theoretical measures to detect communities and connections in complex networks.

  • Recursively divisible numbers

    Generalizing the divisor function to find a new kind of number that can be recursively divided into parts, for use in design and technology.

  • Reprogramming the cell

    Applying mathematical tools to the holy grail of cellular biology: can we produce every type of human cell from within the laboratory?

  • Inference in many dimensions

    Developing a theory of high-dimensional statistical inference using analytic tools from the statistical physics of disordered systems.

  • Collective creativity

    Understanding collective creativity: anonymous collaboration under constrained freedom that transcends the creativity of the individual.

  • Fundamental advances in AI

    Developing radical new approaches to inference and automated decision making using advances in quantum information and statistical physics.

  • The structure of innovation

    Creating a mathematical model of combinatorial innovation to understand how innovation rates can be influenced as components are acquired.

  • Markets and the mind

    Examining the effect of public opinion on stock market returns and harnessing social sentiment to make quantitative market predictions.

  • Bootstrap percolation

    Advancing the mathematical theory of bootstrap percolation, where active cells on a lattice with few active neighbours cease to be active.

  • Sense from social networks

    Developing new local and global measures for networks derived from social interactions to infer social structure, sentiment and behaviour.

  • Surprises from simple rules

    Understanding complex dynamical behaviours generated by simple rules, such as cellular automata, polyominoes and models of competition.

  • Systemic risk

    Applying ideas from diversification and cascading failures to mitigate the propagation of risk across inter-connected institutions.

  • Fractal structures

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

  • Structure of how things relate

    Creating mathematical tools for characterizing the structure of ideal graphs and irregular networks, and the behaviour of processes on them.

  • Technological progress

    Forecasting the rate of technological progress by harnessing empirical regularities captured by Moore’s law and Wright’s law.

  • Extreme pressure surprises

    Simulating the molecular structure of materials under pressures so extreme that we are not yet able to study them in the laboratory.

  • Repairable instead of robust

    Developing a new approach to resilience in which mistakes and unexpected events are mitigated by easy repairs rather than redundancy.

  • Dimension extension

    Reconstructing the 3D shape distribution of rock grains or other randomly packed objects with access to only a 2D slice through them.

  • Reconstructing credit networks

    Using ideas from statistical physics to reconstruct the average properties of financial networks from partial sets of information.

  • Information thermodynamics

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

  • Spectre of hypercubes

    Exploring the spectral properties of subgraphs of the hypercube and Hamming graphs for insights into coding theory and models of evolution.

  • Puzzles in packing

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

  • News and fake news

    Investigating the adverse effects of information asymmetry and deliberate errors in social media and the press, and attempts to remedy them.

  • Fractal heat exchange

    Designing optimal self-similar structures for compact counter-current heat exchange to reduce heating costs and greenhouse emissions.

  • Mathematical medicine

    Creating powerful mathematical methods for predicting the outcomes of diseases that pinpoint the right treatments and speed up drug trials.

  • Is continuous space illusory?

    Creating discrete models of space and spacetime that appear continuous over long lengths and set the stage for non-continuum physics.

  • Remembering to learn

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

  • Economic complexity

    Applying spectral-like theories to the bipartite network of products and capabilities to find latent potential in countries and firms.

  • At the edge of crystals

    Capturing in simulations and mathematical form the surface structure of crystals and how they coalesce when heated but not melted.

  • Intelligence of graphs

    Predicting the behaviour of graphs and processes on them by treating topological patterns as constraints on a random graph ensemble.

  • Alternative universes

    Taming limitations of general relativity, such as the big bang singularity, by formulating theories that admit bouncing or cyclic universes.