POSTDOC RESEARCH ASSOCIATE @ KCL
AHMED
MAGBOOL
I’m Ahmed Magbool, a postdoc research associate at King's College London in the area of Wireless Communications.
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EDUCATION
PhD in Electrical Engineering
University College Dublin
2022 - 2026
Thesis title: Design and Optimization of Wireless Communication and Sensing Systems Assisted by Intelligent Metasurfaces
Research Visit
King's College London
2025
Project: Stacked Flexible Intelligent Metasurfaces for Multiuser Wireless Communications
MSc in Electrical Engineering
King Abdullah University of Science and Technology
2018 -2020
Thesis title: Blind Estimation of Central Blood Pressure Signals from Peripheral Waveforms
BSc in Electrical Engineering
King Fahd University of Petrolium and Minerals
2012 - 2017
PAPERS
PROJECTS
Exploiting structural flexibility in SIM-enabled communications: From adaptive inter-layer spacing to fully morphable layers
King's College London
2025-2026
In this project, we investigated the gain attained from flexibility in SIMs at two levels: (1) flexible inter-layer distances, and (2) fully morphable layers.
RIS-assisted integrated sensing and communications
University College Dublin
2024 - 2026
In this project, we investigated the use of RISs to support the operation of ISAC by manipulating the propagation environment. This also included a study on target privacy in RIS-assisted ISAC.
Improving energy efficiency-fairness tradeoffs in RIS-assisted mmWave communications
University College Dublin
2022-2025
In this project, we investigated the inherent tradeoffs between energy efficiency and user fairness in RIS-assisted mmWave systems, and we proposed resource allocation strategies to improve these tradeoffs.
Terahertz-band NOMA
KAUST
2021-2022
In this project, we investigated the system-level and link-level considerations for THz-band NOMA, including beamforming, clustering, spectrum and power allocation algorithms, channel estimation, data detection, and constraints on computational complexity.
Blind estimation of central blood pressure waveforms from peripheral pressure signals
KAUST
2019-2021
In this project, we proposed a cross-relation approach and a hybrid blind estimation and data-driven method to estimate central blood pressure waveforms from their distorted peripheral counterparts.
CONTACT
Department of Engineering, Strand Building, King's College London, WC2R 2LS London, UK