AI and Computational Bioengineering

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Photograph of Yellow Brimstone Moths taken in Dr Huai-Ti Lin's Neuromechanics and Bioinspired Technologies lab, where researchers are investigating why insects gather at artificial lights.

Image from Dr Guang Yang's lab shows an AI-empowered pulmonary modelling tool that segments lung lobes and airways, combined with an XAI approach to visualise disease patterns associated with severity and mortality.

A student in Professor Aldo Faisal's Brain and Behaviour Lab controls a robotic arm with eye commands to demonstrate how augmenting a robotic arm could extend the range of humans, allowing them to perform more than one task simultaneously.

Our researchers develop and apply AI and computational methods to understand the fundamental mechanisms behind how organisms function and how diseases progress.

Modelling is the process of creating, simplifying, and idealising assumptions to uncover the mechanisms that govern biological systems. It involves both applying existing modelling methodologies to new systems and developing new theoretical frameworks, numerical methods, and simulation platforms that are suitable for capturing the dynamic and stochastic behaviour of specific biochemical or biological systems.

We apply AI and computational bioengineering to design new therapies, improve diagnostics, predict disease progression, and analyse complex data and quantitative modelling.

Anil Bharath
Biologically-inspired computation and inference

Dario Farina
Neural control of movement and signal processing methods for human-machine interfacing

Tom Ouldridge
Principles of biololecular systems

Research highlights

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