Imperial College London


Faculty of EngineeringDepartment of Computing

Research Associate in RF Communications Engineering



m.heggo Website




Huxley BuildingSouth Kensington Campus





Mohammad Heggo received his B.Sc. and M.Sc. degrees in Electrical Engineering from Ain Shams University, Cairo, Egypt in 2006 and 2010, respectively. In 2007, he joined the Research and Development department, Elsewedy Electrometer Company, Egypt as an embedded communication software engineer. In 2013, he was awarded a dual Ph.D. scholarship for four years from the Electrical Engineering and Electronics at the University of Liverpool, UK and the Cognitive Communications Technology Department, Agency for Science, Technology, and Research, Singapore. He was awarded his Ph.D. degree in electrical engineering from the University of Liverpool, UK in 2017. He joined the HOME project as a research associate at the Electrical Engineering and Electronics department, University of Manchester, UK in the period (2017 - 2019), where he studied high electromagnetic field interference to UAVs monitoring offshore windfarms converter stations. Currently, he works as a research associate at the Computing Department, Imperial College of London, UK, where he shares in the development of new RF Machine Monitoring technology known as CogniSense. The new technology is predicted to be a revolutionary step change in condition monitoring for industrial machines. He published 11 papers in high reputable and peer reviewed journals and conferences, spanning different applications of communications and signal processing for future IoT and sensor networks. His research interests include condition monitoring of machines and different electronic devices, signal processing, power line communication, electromagnetic interference to different electrical systems and transmission lines, cognitive radio, MIMO communication systems and smart grid communications.



Heggo M, Sun S, Zhu X, et al., 2019, TV White Space Regulated Broadband Power Line Communication for Point-to-Multipoint Downlink IoT Networks: A Standard Perspective, Ieee Internet of Things Journal, Vol:6, ISSN:2327-4662, Pages:6226-6236

Heggo M, Zhu X, Sun S, et al., 2018, A cognitive TV white space-broadband power line MIMO system for indoor communication networks, Journal of the Franklin Institute-engineering and Applied Mathematics, Vol:355, ISSN:0016-0032, Pages:4755-4770

Heggo M, Xu Z, Sun S, et al., 2017, White broadband power line communication: Exploiting the TVWS for indoor multimedia smart grid applications, International Journal of Communication Systems, Vol:30, ISSN:1074-5351

Heggo M, Zhu X, Huang Y, et al., 2016, Modeling of VHF Current Conversion From Excited Antenna Mode to Differential Mode at Transmission Line Terminals, Ieee Transactions on Electromagnetic Compatibility, Vol:58, ISSN:0018-9375, Pages:1184-1193


Heggo M, Zhu X, Huang Y, et al., 2016, A Hybrid Power Line and TV White Space MIMO System for Indoor Broadband Communications, 84th IEEE Vehicular Technology Conference (VTC-Fall), IEEE, ISSN:2577-2465

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