Geamel Alyami | Engineering and Technology | Best Researcher Award

Published on by Research Hypothesis

Dr. Geamel Alyami | Engineering and Technology | Best Researcher Award

Dr. Geamel Alyami | Engineering and Technology | Best Researcher Award | Associate Research Professor | King Abdulaziz City for Science and Technology | Saudi Arabia 

Dr. Geamel Alyami is a distinguished researcher and engineer specializing in Electrical and Communication Engineering, currently serving at the National Center for Communication Systems and Command and Control Technology within the King Abdul-Aziz City for Science and Technology (KACST), Saudi Arabia. He obtained his Doctor of Science in Electrical Engineering from the Florida Institute of Technology in the United States, where he also earned his Master of Science degree. His academic foundation was laid at the University of Central Florida with a Bachelor of Science in Electrical Engineering, followed by a Diploma in Telecommunication from the Telecommunication and Information College in Jeddah. Throughout his career, Dr. Geamel Alyami has cultivated an extensive background in wireless communication systems, Massive MIMO technology, phased array antennas, and machine learning applications in telecommunication research. His research interests focus on 6G technologies, millimeter-wave communication, channel modeling, predictive antenna systems, and high-efficiency signal processing frameworks that aim to transform global communication infrastructures. With a strong commitment to scientific advancement, Dr. Alyami has contributed to several IEEE-indexed and peer-reviewed international journals and conferences, showcasing impactful work in areas such as multiuser separation, spatial channel modeling, and linear precoding for next-generation communication networks. His technical proficiency includes advanced software and programming tools such as MATLAB, Quartus II, PSpice, VHDL, Verilog HDL, and Microwave Studio, which he effectively integrates into his experimental and theoretical research frameworks. Professionally, Dr. Alyami has accumulated rich industrial and academic experience, having worked with Detecon Al Saudia Co. (DETASAD) as a Transmission SDH/TV Technician, gaining hands-on expertise in telecommunication systems installation, testing, and network optimization. His leadership extends beyond research, as he has actively participated in volunteer and academic communities, including IEEE, Phi Kappa Phi Honor Society, and the Center of Excellence for Telecommunication Applications (CETA). Recognized for his academic excellence, he has been featured on the Dean’s List and received honors from professional engineering societies. Dr. Geamel Alyami’s current research integrates machine learning and predictive modeling for smart THz antennas in 6G systems, reflecting his forward-looking vision for the future of telecommunication engineering. With fluency in Arabic and English and a working knowledge of Spanish, he brings a global perspective to collaborative projects. His unwavering dedication to innovation, leadership, and excellence in communication research underscores his continuing contributions to advancing scientific knowledge and promoting sustainable technology growth in the global research community.

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Featured Publications 

  1. Alyami, G., & Kostanic, I. (2016). On the spatial separation of multiuser channels using 73 GHz statistical channel models. IEEE International Conference on Communication, Networks and Satellite (COMNETSAT). Citations: 12

  2. Alyami, G., Kostanic, I., & Ahmad, W. (2016). Multiuser separation and performance analysis of millimeter wave channels with linear precoding. IEEE International Conference on Communication, Networks and Satellite (COMNETSAT). Citations: 15

  3. Alyami, G., & Kostanic, I. (2016). A low complexity user selection scheme with linear precoding for Massive MIMO systems. IAENG International Journal of Computer Science, 43(3). Citations: 20

  4. Alyami, G., Kostanic, I., & Ahmad, W. (2017). Performance modeling and analysis of millimeter-wave MIMO systems using linear precoding techniques. IEEE Transactions on Wireless Communications. Citations: 25

  5. Alyami, G., & Kostanic, I. (2018). Channel modeling and signal optimization for next-generation millimeter-wave communications. IEEE Access, 6, 12455–12464. Citations: 30

  6. Alyami, G., & Ahmad, W. (2019). Machine learning-assisted beamforming optimization in massive MIMO networks. IEEE Communications Letters, 23(12), 2245–2249. Citations: 35