Assoc. Prof. Dr. Abdalilah Alhalangy | Computer Science | Innovative Research Award

Qassim university | Saudi Arabia

Assoc. Prof. Dr. Abdalilah Alhalangy, Ph.D., is an Associate Professor in Computer Engineering at Qassim University, Kingdom of Saudi Arabia, specializing in advanced areas of artificial intelligence, machine learning, intelligent systems, and cybersecurity. His research spans deep learning, ensemble methods, neural networks, computer vision, wireless networks, cloud computing, big data analytics, robotics, augmented reality, mobile applications, image and video analysis, GIS, and e-learning systems. He has a particular focus on artificial neural networks, wavelet neural networks, fuzzy logic, evolutionary algorithms, and computational intelligence, applied to enhancing the security and functional performance of intelligent systems. Dr. Al-Halangy has published 6 documents cited by 59 Scopus-indexed papers, achieving a Scopus h-index of 3 and an i10-index of 2 on Google Scholar, with a total of 131 citations. His work has earned recognition in fields ranging from Arabic speech emotion recognition and fake account detection in mobile networks to generative AI-driven cybersecurity systems and the evaluation of e-learning effectiveness. Dr. Al-Halangy’s research is characterized by its innovative integration of AI techniques to solve complex real-world problems, positioning him as a leading contributor to modern computing challenges. He has received accolades including the Innovative Research Award for his contributions to the development of secure, intelligent, and efficient computational systems. His work continues to impact both academic research and practical applications, advancing the state of intelligent and adaptive technologies globally.

Publication Profile

Scopus | Orcid | Google Scholar

Featured Publications

• Alhalangy, A., & AbdAlgane, M. (2023). Exploring the impact of AI on the EFL context: A case study of Saudi universities.

• Alhalangy, A. (2024). Deep learning, ensemble and supervised machine learning for Arabic speech emotion recognition. Engineering, Technology & Applied Science Research, 14, 1-10.

• Hassan, A., & Alhalangy, G. I. A. (2023). Fake accounts identification in mobile communication networks based on machine learning. SSRN.

• Alhalangy, A., Elhadi, O. A. M., & Mohamed, E. H. G. (2025). E-learning effectiveness and efficiency in Kassala and Gedaref universities: An IS-impact evaluation. UtilitasMathematica, 122(2), 1301-1317.

• Alhalangy, A. (2025). Generative AI-driven information system for behavioral detection of zero-day cyber attacks. UtilitasMathematica, 122(2), 1194-1210.