BioFuelAi  Ltd was established to commercialise pioneering research developed through the UK Research and Innovation (UKRI) funded project, “Artificial Intelligence Enabling Future Optimal Flexible Biogas Production for Net-Zero” (EP/Y005600/1), led by the University of Surrey under the direction of Professor Michael Short. The £1.4 million EPSRC-funded programme brought together academic and industrial partners across the anaerobic digestion, energy systems, and artificial intelligence sectors to develop advanced AI-driven optimisation technologies for biogas production.

The research focused on solving one of the biggest challenges facing the anaerobic digestion (AD) industry: operational flexibility. Using hybrid machine learning, mechanistic modelling, and real-time optimisation techniques, the project created intelligent digital twins capable of predicting biogas yields, optimising feedstock selection, improving process efficiency, and reducing environmental impacts across AD value chains. The technology enables operators to make faster and more accurate decisions while improving profitability, sustainability, and energy resilience.

The outputs of the UKRI-funded research directly contributed to the formation of BioFuelAi, created to translate these breakthrough research outcomes into commercially deployable software and AI solutions for the global bioenergy sector. BioFuelAi is focused on accelerating the digital transformation of anaerobic digestion and renewable fuel production through advanced optimisation platforms, predictive analytics, and autonomous process intelligence derived from the University of Surrey research programme. The company represents the commercial pathway for technologies and methodologies developed during the EP/Y005600/1 project and associated collaborations with industrial partners including Siemens plc, Future Biogas Ltd, and ALPS Ecoscience UK Limited.

Professor Michael Short is Professor of Process Systems Engineering at the University of Surrey and a leading researcher in artificial intelligence, mathematical optimisation, process systems engineering, and renewable energy systems. His work combines advanced optimisation algorithms, machine learning, and digital process modelling to develop decision-support tools for industrial sustainability and net-zero energy systems.

Professor Short’s research spans bioenergy, distributed energy systems, decarbonisation planning, industrial process control, and AI-enabled operational optimisation. Prior to joining Surrey, he completed his PhD at the University of Cape Town before undertaking postdoctoral research at Carnegie Mellon University, where he worked on advanced process optimisation and industrial modelling projects with global partners including Eli Lilly.

As Principal Investigator of the EP/Y005600/1 project, Professor Short led a multidisciplinary consortium involving universities, industrial technology providers, bioenergy operators, and sustainability specialists. The project produced novel AI and hybrid digital twin technologies capable of dramatically improving the operational performance and economic viability of anaerobic digestion facilities. Research outcomes included advanced recurrent neural network models, hybrid uncertainty-aware prediction systems, and site-wide optimisation algorithms for real-time operational control.

The commercial potential of the BioFuelAi platform and the underlying University of Surrey research has received national recognition through the prestigious Manchester Prize. In 2025, the University of Surrey startup BioFuelAi was shortlisted for the £1 million Manchester Prize (Clean Energy Systems), a major UK government-backed AI innovation competition designed to accelerate breakthrough artificial intelligence solutions that support national economic growth and the transition to net zero.

The Manchester Prize recognition highlights the significance of BioFuelAi’s technology in helping transform renewable gas production, reduce greenhouse gas emissions, and improve energy security through intelligent optimisation of bioenergy infrastructure. The award acknowledgement also demonstrates the successful translation of publicly funded academic research into commercially scalable climate technology with international application.