Paykani Research Group
Scientific AI & Computational Engineering for Energy and Propulsion
School of Engineering and Materials Science · Queen Mary University of London
We combine physics-based simulation and scientific machine learning to study energy and propulsion systems.
Our research spans reactive flows, hydrogen and ammonia combustion, and the cooling of electric machines. We develop computational methods and test them against experiments, working with academic and industrial partners.
Meet the team
Research themes
Reactive flows and combustion
Models of turbulence, chemistry and radiation, including plasma-assisted combustion.
Scientific machine learning
Efficient models for stiff chemical kinetics, with physical constraints and uncertainty estimates.
Hydrogen and ammonia
Combustion chemistry and spray behaviour for engines, turbines and aviation.
Thermal management
Cooling of electric machines through CFD, experiments and design optimisation.
Recent news
Queen Mary to lead the €3.7M ASCEND doctoral network, coordinated by the group, on AI-accelerated modelling for clean energy and propulsion.
Dr Pourya Rahnama joins the group as a Postdoctoral Research Associate.
Leverhulme Trust Research Project Grant awarded for work on non-equilibrium reactive plasmas.
Funding
Our research is supported by EPSRC, the Royal Society, the Leverhulme Trust and Horizon Europe, alongside industrial partners.