About me

Research, evidence and decision-making

I am an equine geneticist and veterinary data analyst, and Programme Coordinator for the postgraduate Equine Science MSc programme at the University of Edinburgh’s Royal (Dick) School of Veterinary Studies. My research and teaching are underpinned by an interest in how we generate, evaluate and use evidence to make better decisions about animal health, performance and welfare.

My research sits at the intersection of equine genetics and genomics, veterinary clinical data, exercise physiology, performance and welfare. I am particularly interested in complex problems where genetics, environment and human management interact, and in developing approaches that bring different forms of evidence together to understand these problems.

For me, evidence-informed decision-making is not simply about having more data. It involves asking good questions, understanding how evidence has been generated, recognising its strengths and limitations, and considering how - and whether - it should be applied to a particular decision. This perspective runs through both my research and my teaching.

From equine practice to molecular research

My research has its roots in equine industry practice. I completed a BA(Hons) in Preclinical Veterinary Studies with Natural Sciences at the University of Cambridge in 2012, before working with the Scottish SPCA and establishing my own business as an equine thermographer. I continued this work alongside an MSc in Equine Science at the University of Edinburgh, graduating in 2017. My MSc research investigated infrared thermography as a potential diagnostic tool for equine myopathies, leading to a continuing interest in equine muscle disease and exercise physiology.

I subsequently completed an MSc in Instrumental Analytical Science at Robert Gordon University, graduating with Distinction in 2018 and specialising in DNA analysis, proteomics and metabolomics. As part of an Erasmus traineeship at the Universidade do Minho in Braga, Portugal, I investigated the role of antioxidant genes in a rapeseed pomace extract treatment for human neurodegenerative disease using C. elegans models. This provided a foundation in molecular genetics and experimental approaches that I later applied to equine disease.

I then completed a PhD at the Royal Veterinary College investigating the genomic architecture of equine exertional rhabdomyolysis (“tying-up”), funded by the RVC’s Mellon Fund for Equine Research and supervised by Dr Androniki Psifidi, Professor Richard Piercy and Dr Emily Clark. My doctoral research combined clinical phenotyping, statistical analysis and genomic approaches to investigate the biological and genetic heterogeneity underlying these complex muscle disorders. I was awarded the 2023 RVC McKeever Prize for the Graduating PhD Student with the Best Original Research Paper.

I am also a Royal Statistical Society accredited Data Analyst, reflecting my interest in combining biological and veterinary expertise with rigorous quantitative approaches.

Research today

My research has broadened from individual diseases to wider questions about equine health, performance and welfare. I am interested in how genetic variation, population history, selective breeding, environment and management influence complex equine traits, and in how clinical and population data can be used to understand these relationships.

I use statistical modelling and genomic approaches to investigate complex and heterogeneous phenotypes, including disease subtyping and predictive analysis using veterinary clinical records. Current research includes systematic review and cross-phenotype meta-analysis of equine genome-wide association studies, population genetics and inbreeding, the effects of selective breeding on health and performance, and research into how genetic information is understood and used by the equestrian community.

My research also increasingly considers what happens when scientific evidence moves from research into practice. This includes work on human behaviour and decision-making around horses, collaboration between equine veterinarians and farriers to support equine wellbeing, and the translation of genetic and veterinary evidence into knowledge that can be used by horse owners, breeders and equine professionals.

Alongside my equine research, I undertake pedagogical scholarship. Current work includes research into the use of generative AI in postgraduate taught programmes and impact of intergovermental accessible virtual education initiatives. This reflects a broader interest in how we teach people to find, evaluate and use evidence in an increasingly data-rich and technologically mediated environment.

Teaching and academic practice

I teach across both postgraduate equine science and genetics, and veterinary medicine. I am Course Leader for the Equine Exercise Physiology and Research Methods and Data Analysis courses on the Equine Science MSc, where I teach muscle physiology, genetics of performance, study design and statistics. I also contribute to teaching in equine reproduction, equine digestion & nutrition, and equine behaviour, welfare & ethics, as well as teaching population and quantitative genetics and genetic evaluation on the Data-Driven Breeding and Genetics MSc.

On the BVM&S programme, I contribute to practical horse husbandry teaching and examining, as well as interviewing. I also supervise postgraduate research projects and am currently a co-supervisor for a PhD investigating food motivation in horses from behavioural and genetic perspectives.

My teaching philosophy is closely connected to my research. I want students to become confident and critical users of evidence: able to formulate good questions, understand how research is designed, evaluate the quality and relevance of evidence, interpret data appropriately, recognise uncertainty and bias, and make reasoned decisions about how evidence should be applied in practice.

I am particularly interested in developing data literacy and in helping students navigate emerging technologies such as generative AI critically and responsibly. I am currently completing a Postgraduate Certificate in Academic Practice at the University of Edinburgh and am an Associate Fellow of the Higher Education Academy.

Academic service and engagement

I contribute to academic service through committee work, peer review, learned-society activities and conference organisation. At the University of Edinburgh, I am a member of the R(D)SVS PGT Teaching and Learning Committee, the R(D)SVS AI Working Group, and I review for the R(D)SVS Veterinary Ethical Review Committee.

I have been involved with the British and Irish Society of Animal Science since 2019, including representing the RVC and subsequently R(D)SVS on the Early Career Council and as EC representative on the Publications Committee. I remain involved in judging the BISAS Undergraduate Thesis of the Year Award, and am a BISAS member on the animal journal family management board as of 2026. I have also contributed to the organisation of the 2024 Edinburgh Next Generation of Genomics Symposium and 2025 & 2027 BISAS Equine Conference, and have organised and chaired conference sessions, including the Genetics session at the BISAS Annual Conference in 2026.

I am also a Royal Statistical Society accredited Data Analyst.

Beyond academia

Outside academia, I am a lifelong horse rider with particular interests in dressage and eventing, and have experience breaking in young horses and coaching young riders. My practical experience with horses continues to inform my interest in the relationship between research evidence and real-world equestrian practice.

I am also an active rugby union referee and was named Scottish Rugby’s 2025 National Community Referee of the Season.

Research Interests

My research focuses on using genetics, genomics, clinical data and quantitative approaches to understand complex problems in equine health, performance and welfare, and on how evidence can be translated into better real-world decisions.

Equine genetics and genomics

• Complex disease, neuromuscular disorders and exertional rhabdomyolysis
• Population genetics, inbreeding and selective breeding
• Genetic influences on health, performance and exercise
• Genome-wide association and cross-phenotype approaches

Veterinary and equine health data

• Statistical modelling and analysis of veterinary clinical data
• Disease phenotyping, subtyping and prediction
• Integration of clinical, phenotypic and genomic data

Performance, welfare and decision-making

• Genetics, environment and management in equine health and performance
• Human behaviour, stakeholder perspectives and decision-making
• Evidence-informed approaches to equine welfare and professional practice

Education, evidence and emerging technologies

• Data literacy, research methods and critical evaluation of evidence
• Evidence-informed teaching and assessment
• Generative AI and technology-enhanced learning in veterinary education