Dr. Ian Jeffrey, P.Eng.

Area

Microwave imaging, computational electromagnetics, inverse problems.

Expertise

Computational electromagnetics, optimization, numerical methods, applied machine learning, applied high-performance computing, applied distributed computing, applied GPU computing.

Dr. Jeffrey develops and applies imaging algorithms as a member of the Electromagnetic Imaging Lab (EIL) at the University of Manitoba. The EIL is an internationally-recognized contributor and pioneer in the advancement of wavefield imaging systems and algorithms. Within this environment, Dr. Jeffrey runs a research program focused on the development and advancement of wavefield imaging algorithms for full-scale applied imaging in agricultural and biomedical applications. These algorithms combine high-performance computing, computational electromagnetics, and machine learning to enable state-of-the-art microwave imaging solutions for biomedical and agricultural applications.

Dr. Jeffrey is an original member of the team of researchers that pioneered the application of electromagnetic imaging for grain storage monitoring. His work has enabled new possibilities in imaging system design and applications by enhancing the capabilities and performance of full-scale quantitative wavefield imaging. Through the EIL these computational advancements are applied directly to the state-of-the-art experimental imaging systems and applications.

Current research interests include time-domain imaging algorithms, generative adversarial networks for system calibration, and using Bayesian machine learning to quantify uncertainty in imaging.

For a list of publications please see Dr. Jeffrey's Google Scholar page:
Google Scholar