Mohammed Farouk Nakmouche

Dr. Mohammed Farouk Nakmouche (Graduate Student Member, IEEE) is currently a Researcher at Huawei Ottawa Research & Development Centre and an affiliated researcher at Toronto Metropolitan University. He completed his PhD in Electrical Engineering at the École de technologie supérieure (ÉTS), Université du Québec, Montreal, Canada, in 2025, where he received the PhD Excellence Award for his dissertation entitled Machine Learning-Aided Design of Additively Manufactured Ridge Gap Waveguide Components.

His doctoral research developed an end-to-end machine-learning-driven synthesis framework for gap waveguide unit cells and microwave components. This work included the generation of a comprehensive electromagnetic dataset covering the 3–300 GHz frequency range and the development of supervised machine learning models capable of predicting suitable geometries from desired electromagnetic performance. The proposed approach significantly reduced the design time of microwave components from hours or days to minutes.

Dr. Nakmouche has a diverse research background bridging RF and microwave engineering, artificial intelligence, additive manufacturing, and telecommunication systems. His expertise covers the analysis, synthesis, and design of RF, microwave, and millimetre-wave components using advanced technologies such as Substrate Integrated Waveguide (SIW), Ridge Gap Waveguide (RGW), additive manufacturing, and heterogeneous material integration.

He has worked as a graduate research student at Canada’s National Research Council (NRC) in Ottawa, where he contributed to the development of 3D-printed flexible antennas and circuits for human monitoring applications. He has also contributed to several international research projects in France, Turkey, Egypt, Taiwan, and Canada, which helped him develop broad technical experience in microwave and millimetre-wave hardware.

His current research interests include inverse problem analysis, machine-learning-aided synthesis, generative models for inverse RF design, explainable artificial intelligence for electromagnetic optimisation, and AI-assisted design methodologies for antennas and passive microwave components.

Dr. Nakmouche has authored and reviewed articles for IEEE journals and conferences and has presented invited talks on machine-learning-assisted electromagnetic design. He currently leads the IEEE MTT-S Student Ambassador Program and is actively involved in mentorship, outreach, and young-professional engagement. Through his technical and volunteer activities, he encourages young engineers and researchers to embrace artificial intelligence, advanced manufacturing, and emerging microwave technologies to accelerate innovation in antenna and passive RF component design.