Dr. Peter McKeown will serve as Lead Translational Researcher for this project. He is a Lecturer (Above the Bar) in Plant & AgriBiosciences at the University of Galway and has built a strong reputation in the areas of plant genetics, reproductive biology, and epigenetic regulation of relevance for sustainable crop breeding. His academic pathway from an MSc in Plant Breeding and Biotechnology at the John Innes Centre, UK to a PhD in plant cell biology provides the scientific foundation for the AgriFuTech project, rooted as it in genomic prediction and multi-omics interpretation. Peter’s work has examined polyploidy, heterosis, genome dosage effects, and epigenomic regulation, with publications that span both fundamental discovery and applied breeding research. As coordinator of the MSc in Climate Change, Agriculture, and Food Security, he has also demonstrated strong leadership in shaping research training within agri-innovation. His background ensures that the biological assumptions, datasets, and end-user needs are fully integrated into AgriFuTech’s development.
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Research Themes:
Sustainability & Environmental Management
Research Programmes
AgriFuTech
An AI genomic prediction engine that learns directly from complex, noisy datasets to deliver reliable trait predictions across crops and environments.
AI-Driven Energy Prediction and Workload Placement
Predicts the energy a computing workload will use before it runs, helping data centres cut costs, reduce emissions and meet EU reporting rules.
AI-Sprayer
A chemical-free precision weeding, fertigation and irrigation platform for organic farms, using computer vision to target hot water at individual weeds.
