Ayed M. Alrashdi
- Ph.D. Student (former), Electrical and Computer Engineering
- M.S. (former), King Abdullah University of Science and Technology
Ph.D. degree in electrical and computer engineering from the King Abdullah University of Science and Technology (KAUST) working with Professor Tareq Al-Naffouri in the Information System Lab (ISL),Assistant Professor with the Electrical Engineering Department at University of Ha'il
Research Interests
- Statistical signal processing.
- High dimensional statistics.
- Compressed sensing.
- Statistical learning.
- Wireless communications.
- Mathematical optimization.
Awards and Distinctions
- Prince Saud Bin Abdulmuhsin Award for ranking first on the graduating class , University of Hail, 2014
Qualifications
Education
- Doctor of Philosophy (Ph.D.)
- Electrical and Computer Engineering, King Abdullah University of Science and Technology (KAUST), Saudi Arabia, 2021
- Master of Engineering (MEng)
- Electrical Engineering, King Abdullah University of Science and Technology (KAUST), Saudi Arabia, 2016
- Bachelor of Engineering (B.Eng.)
- Electrical Engineering, University of Hail, Saudi Arabia, 2014
- Arabic
- Native or bilingual proficiency
- English
- Full professional proficiency
Languages
Quote
KAUST is a great research environment. I'm fortunate to have the opportunity to work with world-class researchers and scientists every day!
Selected Publications
- Ma, X. ., Kammoun, A. ., & Ballal, T. . (2023). Asymptotic Performance Analysis of the Regularized Least Squares Precoding with Restricted Transmit Power in Multi-User Massive MIMO. 2023 31st European Signal Processing Conference (EUSIPCO). Presented at the. Helsinki, Finland: IEEE.
- Alrashdi, A. ., Alazmi, M. ., & Alrasheedi, M. A. (2023). Generalized Penalized Constrained Regression: Sharp Guarantees in High Dimensions with Noisy Features. MDPI.
- Alrashdi, A. ., & Sifaou, H. . (2022). Performance Analysis of Regularized Convex Relaxation for Complex-Valued Data Detection. MDPI.
- Alrashdi, A. M., Alrashdi, A. M., Alghadhban, A. ., & Eleiwa, M. A. H. (2022). Optimum GSSK Transmission in Massive MIMO Systems Using the Box-LASSO Decoder. IEEE Access ( Volume: 10).
- Alrashdi, A. ., Sifaou, H. ., Kammoun, A. ., Alouini, M.-S. ., & Al-Naffouri, T. Y. (2020). Box-Relaxation for BPSK Recovery in Massive MIMO: A Precise Analysis under Correlated Channels. ICC 2020 - 2020 IEEE International Conference on Communications (ICC). Presented at the. Dublin, Ireland: IEEE.
