Currently funded research
Below is a list of the projects and researchers we currently fund. We support research beyond the initial funding to ensure it continues to develop and deliver impact.
AI-assisted personalisation of neurostimulation
Petra Fischer and Conor Houghton
Faculties of Health and Life Sciences, Science and Engineering
Schools of Psychology and Neuroscience, Engineering Mathematics and Technology
AI-assisted personalisation of neurostimulation
Petra Fischer and Conor Houghton
Faculties of Health and Life Sciences, Science & Engineering
Schools of Psychology and Neuroscience, Engineering Mathematics and Technology
AI-Organoid: A Smart Predictive Platform for Advanced Neurological Modelling
James Armstrong and Qiang Liu
Faculties of Health and Life Sciences, Science and Engineering
Bristol Medical School, School of Engineering Mathematics and Technology
An AI-integrated lung-on-a-chip platform for the rapid screening and optimisation of mesenchymal stem cell secretome therapeutics
Wael Kafienah, Lucia Marucci and Darryl Hill
Faculties of Health and Life Sciences, Science and Engineering
Biochemistry & Cellular & Molecular Medicine, Engineering Mathematics and Technology
An Integrated AI and machine learning platform to enable high throughput, precision oncology driven drug testing. Cancer, Engineering Biology
Deepali Pal, Colin Campbell, Stephen Cross, Stephen Cross, Rihuan Ke
Faculties of Health and Life Sciences, Science and Engineering
Biochemistry & Cellular & Molecular Medicine, Engineering Mathematics and Technology, Wolfson Bioimaging Unit, School of Mathematics
Automated image analysis to facilitate the incorporation of quality assurance measures into surgical RCTs
Natalie Blencowe, Michael Wray, Anni King, Sheraz Marker and Nainika Meno
Faculties of Health and Life Sciences, Science and Engineering
Bristol Medical School, School of Computer Sciences, Bristol Medical School, University of Oxford
Bristol Respiratory Infection Dashboard (BRID Project)
Andrew Dowsey, Raul Santos-Rodriguez
Faculties of Health and Life Sciences, Science and Engineering
Bristol Vet School, Engineering, Mathematics and Technology
Explainable AI for Early Categorisation of Child Deaths: Real-Time Insights for Prevention
Karen Luyt, Edwin Simpson, Brian Hoy, James Gospill and David Odd
Faculties of Health and Life Sciences, Science and Engineering
Bristol Medical School, Mathematics and Technology, Electrical, Electronic and Mechanical Engineering, Cardiff University - School of Medicine
Genetic Doppelgangers: Using AI to Reveal the True Face of Streptococcal Disease
Alice Halliday, Colin Campbell, Rachel Bromell, Anu Goenka and Sion Bayliss
Faculties of Health and Life Sciences, Science and Engineering
Biochemistry & Cellular & Molecular Medicine, Engineering Mathematics and Technology, Bristol Medical School, Bristol Vet School
Investigating practices around antimicrobial prescribing in Harare, Zimbabwe
Jack Stanley
Faculty of Health and Life Sciences
Bristol Medical School
Mental Health in Young People
Myles-Jay Linton
Faculty of Health and Life Sciences
Bristol Medical School
Predicting PD-L1 Status From H&E Slides Using AI
Tom Dudding, Qiang Liu, Sarah Hargreaves & Miranda Pring
Faculties of Health and Life Sciences, Science and Engineering
Bristol Dental School, School of Engineering Mathematics and Technology
Predictors of mental health problems in autism
Laura Hull
Faculty of Health and Life Sciences
Bristol Medical School (Population Health Science)
Preventing anxiety and depression in schools: Co-production of a novel arts-based programme
Naomi Warne
Faculty of Health and Life Sciences
Bristol Medical School
Rational AI Driven Target Acquisition from Genomes (RAIDTAG)
Darryl Hill and Sean Davis
Faculties of Health and Life Sciences, Science and Engineering
Schools of Cellular and Molecular Medicine, Chemistry
Training Azerbaijani paediatricians in communicating about vaccinations with caregivers – AzPIC Study
Emma Anderson
Faculty of Health and Life Sciences
Bristol Medical School
Updated 8 October 2025