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AI and Computational Bioengineering

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.

Pedro Ballester
Computational drug design and AI modelling for precision oncology

Anil Bharath
Biologically-inspired computation and inference

Sonja Billerbeck
Turning microbial functions into applications using engineered biology and computational tools

Etienne Burdet
Sensorimotor control and learning

Hayriye Cagnan
Theoretical models of brain circuits

Claudia Clopath
Computational neuroscience

Aldo Faisal
Machine and biological learning, human augmentation, human-robot interaction, human-AI interfacing

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

Richard Kitney
Engineering biology, synthetic biology, biological standards and data sharing

Holger Krapp
Systems neuroscience in insects: multisensory integration, sensorimotor transformation

Pete Lally
Developing image acquisition and reconstruction techniques using MRI physics

Rodrigo Ledesma-Amaro
Development and application of computational and AI-based engineering biology tools

Chiu Fan Lee
Biophysics of pattern formation

Huai-Ti Lin
Neuromechanics and bio-inspired technologies

Nic Newell
Developing computational models of the spine to understand injury and assess implant design

Tom Ouldridge
Principles of biololecular systems

Reiko Tanaka
Computational systems biology and medicine

Julien Vermot

Guang Yang
Multimodal Information Fusion, Synthetic Data, and Digital Twins

Choon Hwai Yap
Cardiac developmental biomechanics

Dandan Zhang
Biomedical and bio-inspired micromanipulation, human-robot interaction, multimodality sensing

Research highlights

More Bioengineering news

Brain waves of Formula E world champion measured on Top Gear race track

EczemaPred: A computational framework for personalised prediction of eczema severity dynamics

Inferring fungal growth rates from optical density data