Dr Amin Nadimy
Postdoctoral Research Associate in AI Surrogate Models for Forward Stratigraphic Modelling
Email: a.nadimy@qmul.ac.uk
Profile
Amin Nadimy is a Postdoctoral Research Associate at the Digital Environment Research Institute (DERI), working on the development of fast, physics-informed surrogate models for forward stratigraphic modelling as part of a collaborative project with TotalEnergies. His work focuses on applying Physics-Informed Neural Networks (PINNs) to emulate computationally intensive fluid flow simulations within the CRONOS framework.
Amin holds a PhD in Computational Fluid Dynamics (CFD) from Imperial College London, where he developed convolutional neural network surrogate models for large-scale fluid dynamics problems. His research spans environmental and energy applications, including flood modelling, offshore wind turbine simulation, and hydrological modelling integration in industry platforms.
With a BEng in Petroleum Engineering and a background in geological and sedimentary systems, he bridges geoscience with AI-driven modelling. He has previously worked with BP, Moody’s, and SaferPlaces, and remains active in scientific outreach and teaching in programming, data science, and numerical modelling.