Paykani Group
Reactive Flows, Computational Modelling, Scientific Machine Learning (SciML), Thermal Management .
School of Engineering and Materials Science · Queen Mary University of London
220, Engineering Building
Queen Mary University of London
Mile End Road, London E1 4NS
We develop data-driven and physics-based methods for energy and propulsion systems. Our work sits at the interface of combustion modelling and scientific machine learning, and is directed at a single question: how do we make the numerical modelling of chemically reactive flows fast enough, and accurate enough, to design the zero-carbon propulsion systems the energy transition requires?
The group works across four connected themes — reactive flow and combustion modelling, machine learning for combustion, hydrogen and ammonia as sustainable fuels, and the thermal management of electric machines. We are supported by EPSRC, the Royal Society, the Leverhulme Trust and Horizon Europe, and collaborate with partners at ETH Zürich, Kyushu University, Cardiff University and across the UK automotive and aerospace sectors.
The group is led by Dr Amin Paykani, Senior Lecturer in Sustainable Propulsion Systems and Research Lead of the Centre for Intelligent Transport at Queen Mary University of London.
Interested in joining? See opportunities for PhD, postdoctoral and visiting positions.
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