Dr. Khalil earned his Ph.D. in Systems Engineering and Computers from Al-Azhar University with research focused on cloud robotic frameworks for multi-robot task coordination. He also completed his Master’s degree in Systems Engineering and Computers with specialization in FPGA applications for model predictive control. His Bachelor’s degree in Systems and Computers Engineering was awarded with honors. His educational background established advanced expertise in Artificial Intelligence, robotics, control systems, embedded computing, and intelligent engineering technologies.
Professional Experience
Dr. Khalil has extensive academic and industrial experience in Artificial Intelligence, Systems Engineering, and intelligent technologies. He currently serves as Associate Professor at Ahliyya Amman University and previously worked at Al-Azhar University, Innovation University, Canadian International College, and Misr University for Science and Technology. His responsibilities include teaching, postgraduate supervision, laboratory management, curriculum development, and quality assurance. He also gained industrial experience as a System Engineer in engineering and technology organizations.
Awards and Honors
Dr. Khalil has received recognition for his academic excellence, research productivity, and contributions to Artificial Intelligence and engineering education. He has held several leadership and quality assurance positions including Director of the College Quality Unit and member of academic accreditation committees. He actively participates in international conferences, engineering workshops, and professional training programs in Deep Learning, TensorFlow, Generative AI, and Data Science. His growing international publication profile reflects continuous scientific and technological advancement.
Research Interest
Dr. Khalil’s research focuses on Artificial Intelligence, Deep Learning, cloud robotics, cybersecurity, embedded systems, IoT, FPGA systems, and intelligent communication technologies. His recent work emphasizes network intrusion detection, hardware trojan detection, fog-cloud computing, reinforcement learning, wireless network optimization, and AI-enabled intelligent systems. He is also interested in robotics, control engineering, data science, and healthcare image analysis. His interdisciplinary research integrates advanced AI methodologies with practical engineering applications to solve modern technological challenges.
Publication Top 5
1. Leveraging Transformer Networks for Enhanced Detection of Hardware Trojans via Power Side-Channel Analysis
Year: 2026
Citation: IEEE Access
2. Novel Transformer-Based Model for NID in Fog Computing Environment
Year: 2026
Citation: Scientific Reports
3. A Siamese Deep Learning Framework for Efficient Hardware Trojan Detection Using Power Side-Channel Data
Year: 2024
Citation: Scientific Reports
4. A Smart IoT-Based Home Automation System for Controlling and Monitoring Home Appliances
Year: 2023
Citation: International Review of Automatic Control
5. A Hybrid Decentralized Coordinated Approach for Multi-robot Exploration Task
Year: 2018
Citation: The Computer Journal
Conclusion
Khalil Mohamed Khalil AbdElnaby has established a strong academic and research profile in Artificial Intelligence, Intelligent Systems, Cloud Robotics, Cybersecurity, and Embedded Computing. His contributions to high-impact research, postgraduate supervision, engineering education, and interdisciplinary innovation demonstrate significant professional excellence. With internationally indexed publications, growing citation impact, and active involvement in advanced AI-driven technologies, he continues to contribute meaningfully to modern computing research and engineering applications at both academic and industrial levels.