Assoc. Prof. Akram Al-Hourani

Associate ProfessorProgram Manager for Telecom Engineering Master Degree

Biography

A/Prof Akram Al-Hourani (PhD, BEng, MBA, SMIEE), Is an Associate Professor and the Telecommunication Program Manager (Masters) at the School of Engineering, RMIT University. He obtained his PhD in 2016 from RMIT University. Prior joining academia, he had extensively worked in the ICT industry as an R&D engineer, radio network planning engineer and then as an ICT program manager for several projects spanning over different technologies; including mobile networks deployment, satellite networks, and railway ICT systems. The total value of industry projects directed by A/Prof Al-Hourani exceeded $120M.

He has extensive industry / government engagement as a chief investigator in multiple research projects related to The Internet-of-Things (IoT), Radar systems, Satellite SAR / Satellite Communications. As a Lead Chief Investigator, he provided key expertise in delivering the largest open (Internet-of-Things) network in Victoria in collaboration with 5 local governments “Northern Melbourne Smart Cities Network”, this project attracted two prestigious industry awards from the Municipal Association of Victoria (MAV) "Technology Awards for Excellence 2020", and the IoT Alliance Australia (IoTAA) "Smart Cities Award for 2020"

He published more than 96 journal articles and conference proceedings, including 3 book chapters (See ORCID link 0000-0003-0652-8626), A/Prof Al-Hourani has won the IEEE Sensors Council Paper Award for his contribution in hand-gesture recognition using neural networks. He is currently listed in Stanford University's list of top 2% scientists in both Career-Long list and Single Year Impact list for 2021, A/Prof Al-Hourani is currently an Associate Editor in IEEE Transactions of Aerospace and Electronics, and in Frontiers in Space Technologies and an Editor in MDPI Remote Sensing Journal. His current research interests include Satellite Communications, Radars Systems, UAV Communication Systems, Signal Processing / Machine Learning, and Stochastic Geometry.

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