Dr. Aida Al-Samawi, an Assistant Professor in the Department of Computer Networks at King Faisal University, Al-Ahsa, Saudi Arabia, hails from Yemen. Her remarkable contributions in the field of Telecommunication have earned her the prestigious Women Researcher Award. 🏆 With her expertise, Dr. Al-Samawi is pioneering advancements in telecommunications, driving innovation, and empowering women in STEM fields. Her dedication and leadership serve as an inspiration, fostering a culture of excellence in research and academia. Dr. Al-Samawi’s commitment to advancing technology and promoting diversity highlights her as a trailblazer in the field, shaping the future of telecommunications.
Profile
Scopus
Education 📚
Aida Isamail Ahmed Al-Samawi pursued her academic journey with dedication and excellence. She obtained her Ph.D. in Communications and Network Engineering from the University Putra Malaysia, Malaysia. Prior to that, she completed her MSc. in Computer Science and her BSc. in Mathematics/Computer Science, both from the same institution. This robust academic background equipped her with the necessary skills and knowledge to excel in her field.
Experience 💼
Dr. Al-Samawi has a wealth of experience in academia and professional training. She currently serves as an Assistant Professor in the Faculty of Computer Science and Information System at King Faisal University, KSA. Her previous roles include positions at Jadara University, IUTT, and various institutes in Yemen, where she contributed significantly to education and training in computer science and network engineering.
Research Interests 🔬
Dr. Al-Samawi’s research interests span diverse areas within the realm of technology, with a focus on Cybersecurity, Telecommunication, Wireless communication, Signal processing, and Mathematical modeling. Her passion for exploring innovative solutions to real-world problems drives her research endeavors.
Publications Top Notes 📚
“CNN-GMM Approach to Identifying Data Distribution Shifts in Forgeries” – 2024
“Novel Machine Learning Approach for DDoS Cloud Detection” – 2024
“Variational Optimization for Sustainable Massive MIMO Base Station Switching” – 2024
“Advancing Network Security with AI: SVM-Based Deep Learning for Intrusion Detection” – 2023
“Intrusion Detection Techniques in Social Media Cloud: Review and Future Directions” – 2023