Intelligent Electromagnetics (Intellem) solves complex electromagnetic (EM) problems through advanced numerical modelling and artificial intelligence (AI).
We combine three decades of research in ground penetrating radar and computational electromagnetics with modern machine learning to deliver practical, validated results — whether you need a simulation built, a dataset interpreted, a model trained, or your team brought up to speed.
Harnessing advanced numerical modelling, we simulate electromagnetic wave propagation in complex, realistic environments: antenna design and optimisation, digital twins of commercial GPR systems, and challenging problems with high societal value such as landmine and UXO detection.
We provide Ground Penetrating Radar (GPR) and geophysical services to map the subsurface and assess critical infrastructure — from data processing and interpretation to advanced, physics-based analysis that gets more out of your GPR data.
We apply machine learning where conventional methods fall short: synthetic training data generated from physics-based simulation, fast-forward solvers, automated interpretation, and full-waveform inversion — with data preparation and model training tailored to your problem.
We run workshops and bespoke training on numerical modelling with gprMax, digital twins, GPR processing and interpretation, machine learning, and full-waveform inversion. We also develop custom software — including gprMax extensions and support — to fit your workflow.
Dr Craig Warren, Professor Antonis Giannopoulos, and Dr Iraklis Giannakis formed Intelligent Electromagnetics in 2021, having developed extensive expertise in advanced numerical modelling coupled with artificial intelligence to solve complex electromagnetic wave propagation problems.
Lead developer of gprMax. Chartered Engineer (CEng), FICE, FHEA.
Craig's research on GPR for infrastructure sensing and geophysical applications led to the first numerical models of commercial GPR antennas — digital twins that let GPR responses be simulated far more accurately, moving data interpretation from qualitative towards quantitative. He leads the development of gprMax, which has been selected for Google Summer of Code six times since 2019. Craig co-chaired IWAGPR 2017 and has delivered GPR modelling workshops worldwide.
Creator of gprMax. More than 30 years in GPR modelling.
Antonis is an internationally recognised expert on GPR modelling and its applications. One of the pioneers of numerical modelling of GPR in the early 1990s, he created gprMax, which has since become the de facto tool in the field. He continues to lead research into the underlying EM modelling methodologies and has directed major projects — supported by the Defence Science and Technology Laboratory (Dstl) and Google Fiber (USA) — that have advanced the accuracy and performance of GPR simulation. He has more than 150 publications on GPR modelling, is a regular invited speaker internationally, and was General Chair of IWAGPR 2017.
Near-surface geophysics, GPR modelling and machine learning. Bullerwell Lecturer 2024.
Iraklis's work on modelling heterogeneous and dispersive materials brought a new level of realism and accuracy to GPR simulation, and his signal-processing, full-waveform inversion (FWI) and machine learning methods have significantly improved and automated the interpretation of GPR data. He won best paper at the 15th International Conference on GPR, and his research on planetary GPR has featured in The Independent, The Conversation and Phys.org.
Tell us about your problem. We scope work flexibly — from a day of expert review to multi-month research and development — and we're always happy to start with an informal conversation.
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