
Professor Andrew Dowsey
MEng(Lond.), PhD
Current positions
Chair in One Health Data Science
Bristol Veterinary School
Contact
Press and media
Many of our academics speak to the media as experts in their field of research. If you are a journalist, please contact the University’s Media and PR Team:
Research interests
Andrew’s research group focuses on the acceleration of health sciences research and new clinical diagnostics through novel artificial intelligence and statistical data science methodology, as well as data collection and management platforms. His team works in highly multidisciplinary environments to both lead and support investigations across three strands of research: Profiling the protein and metabolite content of biological fluids and tissues using mass spectrometry proteomics and metabolomics for understanding disease mechanism, and to discover biomarkers for clinical diagnostics; Constructing secure research platforms and developing predictive models from population-level health and environmental data to develop interventions for One Health challenges such as anti-microbial resistance; Intensive longitudinal health, activity and behavioural monitoring at the level of individual animals and groups of animals for welfare and environmental sustainability.
Andrew has a joint position in Bristol Veterinary School and the Department of Population Health Sciences, Bristol Medical School. He is AI lead for the John Oldacre Centre at Bristol Veterinary School, where he is also Population Health Theme Lead and Impact Director. He is Director for Enterprise & Impact in the Faculty of Health Sciences, Fellowships Director for the EPSRC LEAP Digital Health Hub. Previously, he was Research Director for Bristol Veterinary School, founding Director of the John Oldacre Centre,an Associate Director of the HDR-UK South-West Better Care Partnership and a Turing Fellow. He has received a MICCAI Young Scientist award, held an EPSRC Overseas Postdoctoral Fellowship at the Life Sciences Interface between the Hamlyn Centre, Imperial College London, University of Texas MD Anderson Cancer Center and University College Dublin, an MRC New Investigator Research Grant at the Centre for Advanced Discovery and Experimental Therapeutics, The University of Manchester, and was a Reader in the Department of Electrical Engineering and Electronics at the University of Liverpool.
Current Staff
- Axel Montout (PDRA)
- Jing Gao (PDRA)
- Marco Ramirez Montes de Oca (Senior PDRA)
- Léo Gorman (JGI Data Science Specialist)
- Rita Rodrigues Rasteiro de Campos (JGI Research Software Engineer)
Current Postgraduate Students (Main Supervisor; PhD unless specified)
- Tim Dong
- Ed Barker (EPSRC CDT in Digital Health)
- Asheesh Sharma (joint with Melvyn Smith, UWE; BBSRC SWBio CDT)
- Harry Tata (EPSRC COMPASS CDT; funded by AstraZeneca)
- Dan Milner (EPSRC COMPASS CDT; joint funded by ILRI)
- Yuijie Dai (EPSRC CDT in Digital Health)
- Meng Du (GW4 BioMed MRC DTP)
- Daria Baran (Bristol PhD Scholarship)
- Brooke Bennett (MScR; funded by The Langford Trust)
- Huimin Liu (China Scholarship Council)
Current Postgraduate Students (Co-supervisor; PhD unless specified)
- Abbie Williams (lead Laura Peachey; BBSRC SWBio CDT)
- Elliot Stanton (lead Kristen Reyher; BBSRC SWBio CDT)
- Sara Hall (lead Daniel Enriquez-Hidalgo; BBSRC SWBio CDT)
- Mike Nsubuga (lead Sion Bayliss; BioMed MRC DTP)
- Aimee Daum (lead Matthew Avison; Bristol PhD Scholarship)
- Amy Fitzgerald (lead Carlos Garcia de Leaniz; joint funded by Swansea University & Visifish)
- Caroline Schreiber (lead Sion Bayliss; BioMed MRC DTP)
- Amy Fitzgerald (lead Carlos Garcia de Leaniz; joint funded by Swansea University & Visifish)
- Bruno Carlos Ramos (lead Carlos Garcia de Leaniz; BBSRC SWBio CDT)
Graduated Postgraduate Students
- Tom Zuffa PhD (2024), "Investigation of factors associated with successful completion of Fédération Équestre Internationale endurance rides and of risk factors for and prediction of post-race lameness and unacceptable performance in Thoroughbred flat racing at The Hong Kong Jockey Club"
- Léo Gorman PhD (2024), "Leveraging the power of household surveys in agricultural research for development"
- Axel Montout PhD (2023), "Prediction of poor health in small ruminants and companion animals with accelerometers and machine learning"
- Lucy Vass PhD (2023), "Statistical modelling methodology for investigating risk factors of antimicrobial use and resistance: applied to UK dairy farms"
- Jon Massey PhD (2021), "Barriers to population-level AMR research in UK livestock and opportunities for data science"
- Al Phillips PhD (2020), "Bayesian methods for protein quantification in mass spectrometry proteomics"
Alumni
- Brian Sullivan (Senior PDRA)
- Ranjeet Bhamber (Research Fellow)
- Gina Caplen (Senior PDRA)
- Jo Hockenhull (Senior PDRA)
- Louis MacGregor (Senior PDRA)
- Will Andrew (PDRA)
- Hanqing Liao (PDRA)
- Andris Jankevics (PDRA)
- Yan Zhang (PDRA)
Projects and supervisions
Research projects
AI to monitor changes in social behaviour for the early detection of disease in dairy cattle
Principal Investigator
Managing organisational unit
Bristol Veterinary SchoolDates
01/07/2023 to 30/06/2026
8055 (MRC CiC Ref MC_PC_19031 additional funding) Health Sciences Enterprise and Innovation Mentorship programme 2022
Principal Investigator
Managing organisational unit
Bristol Veterinary SchoolDates
01/09/2022 to 31/03/2023
HDR-UK South West Better Care Partnership
Principal Investigator
Role
Co-Investigator
Description
Better Care South-West Partnership is a collaboration of NHS commissioners, primary, secondary, community and mental health care providers, local authorities, and academia. They look to address real-world health problems using…Managing organisational unit
Bristol Medical School (PHS)Dates
01/05/2020 to 31/03/2023
Building Open Data Standards for Livestock Veterinary Treatment Data
Principal Investigator
Role
Collaborator
Description
Extension of ICAR Animal Data Exchange standards to include key data regarding livestock veterinary treatments with particular focus on UK context.Managing organisational unit
Bristol Veterinary SchoolDates
01/08/2018
Closed 8055 Belgium: Taming the application of statistics in proteomics and metabolomics BB/R021430/1
Principal Investigator
Managing organisational unit
Bristol Veterinary SchoolDates
11/07/2018 to 31/12/2019
Thesis supervisions
Investigation of factors associated with successful completion of Fédération Équestre Internationale endurance rides and of risk factors for and prediction of post-race lameness and unacceptable performance in Thoroughbred flat racing at The Hong Kong Jockey Club
Supervisors
Barriers to population level AMR research in UK livestock and opportunities for data science
Supervisors
How do dogs respond to olfactory changes associated with human health and stress?
Supervisors
Leveraging the Power of Household Surveys in Agricultural Research for Development
Supervisors
Statistical modelling methodology for investigating risk factors of antimicrobial use and resistance
Supervisors
Prediction of poor health in small ruminants and companion animals with accelerometers and machine learning
Supervisors
Publications
Selected publications
01/06/2021Visual identification of individual Holstein-Friesian cattle via deep metric learning
Computers and Electronics in Agriculture
Widespread severe cerebral elevations of haptoglobin and haemopexin in sporadic Alzheimer's disease
Biochemical and Biophysical Research Communications
Uncertainty aware protein-level quantification and differential expression analysis of proteomics data with seaMass
Statistical Analysis of Proteomic Data
Recent publications
10/03/2025Comparing conventional and Bayesian workflows for clinical outcome prediction modelling with an exemplar cohort study of severe COVID-19 infection incorporating clinical biomarker test results
BMC Medical Informatics and Decision Making
Machine Vision Applications for Welfare Monitoring in Aquaculture
Aquaculture, Fish and Fisheries
Novel characterisation of dairy herds in Wales
Preventive Veterinary Medicine
Universal bovine identification via depth data and deep metric learning
Computers and Electronics in Agriculture