Muhammad Shehab

PhD Student in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 36th cycle (2020-2023)
Department of Electronics and Telecommunications (DET)



Thesis title

On Applications of Machine Learning In IRS NOMA Architectures For 5G and Beyond

Research topic

On Applications of Machine Learning In IRS NOMA Architectures For 5G and Beyond


Research presentation


Research interests

Big Data, Machine Learning, Neural Networks and Data Science
Communication and Computer Networks
Radio frequency and microwave electronics


Muhammad Shehab, an IEEE member since 2019, was born on April 20, 1985, in Ra's-Beirut, a district within Beirut city, Lebanon. He earned his Bachelor of Engineering (B.E.) and Master of Electrical/Communication and Electronics Engineering (M.E.) degrees from Beirut Arab University (BAU) in 2007 and 2011, respectively. Later, he joined the Faculty of Electrical Engineering, Qatar University (QU), Qatar, in 2018, and the Department of Electronics and Telecommunications, Politecnico di Torino (POLITO), to continue his study to towards his Doctor of Philosophy (Ph.D.) degree. in the field of Wireless Communication. In 2013, he joined the Department of Information Technology, Community College of Qatar (CCQ), as a Network Engineer Lecturer till date. His research interests span a wide array of subjects, including 5G and 6G Networks, Non-orthogonal multiple access (NOMA), Intelligent reflecting surface (IRS), mmWave, THz, Massive MIMO, Beamforming, Machine learning (ML), Deep reinforcement learning (DRL), Long Range (LoRA), Satellite communication, and sustainability in 5G networks and smart cities. He has actively collaborated with researchers in Italy, Qatar, and internationally.

Awards and Honors

  • Qatar Foundation - Researchers Exchange and Mobility Program (REMP) - The award was withdrawn due to COVID-19. (2023)


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