Researcher, Royal Military College of Canada, Canada
🎓 Nordine Quadar, P.Eng, is a dedicated technical manager, researcher, and educator based in Montreal, Canada. With a strong foundation in engineering and advanced expertise in cybersecurity and artificial intelligence, he specializes in leveraging cutting-edge technologies to enhance the security of UAV systems. Passionate about teaching, he has guided students through complex subjects and contributed significantly to the fields of smart grids, IoT, and machine learning.
Publication Profile
Google Scholar
Education
📚 Nordine Quadar holds a PhD in Computer Science (in progress, 2022–2025) from the Royal Military College of Canada, supervised by Abdellah Chehri, focusing on UAV cybersecurity using Edge AI. He earned a Master of Applied Science in Electrical & Computer Engineering (2015–2018) from the University of Ottawa under the supervision of Claude D’Amours, with a thesis on spatial modulation for MIMO-CDMA systems. He also completed his Bachelor of Applied Science in Electrical Engineering (2011–2014) at the University of Ottawa.
Experience
💼 Technical Expertise defines Nordine’s career. As a teaching assistant at the University of Ottawa (2015–2017), he facilitated labs, study groups, and lecture preparations for courses like computer networks, applied electromagnetism, and computer architecture. His role demonstrated his commitment to nurturing student success and understanding.
Research Interests
🔍 Nordine’s research interests center on cybersecurity, AI-powered intrusion detection systems, digital twins for smart grids, and IoT testbeds. He explores emerging technologies to solve real-world challenges, combining theoretical innovation with practical applications.
Awards
🏆 Nordine has earned recognition for his impactful contributions to engineering and research, highlighting his commitment to excellence in academia and technical leadership.
Publications
N. Mchirgui, N. Quadar, et al. The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review. Applied Sciences, 2024. DOI:10.3390/app142310933
N. Quadar, A. Chehri, et al. Intrusion Detection Systems in Automotive Ethernet Networks: Challenges, Opportunities and Future Research Trends. IEEE Internet of Things Magazine, 2024, Vol. 7, No. 2, pp. 62–68.
N. Quadar, M. Rahouti, et al. IoT-AI/Machine Learning Experimental Testbeds: The Missing Piece. IEEE Internet of Things Magazine, 2024, Vol. 7, No. 1, pp. 136–143.
N. Quadar, H. Chaibi, et al. Recommendation Systems: Models, Techniques, Application Fields and Ethical Challenges. In Proceedings of the 7th International Conference on Big Data and Internet of Things (BDIoT ’24), 2024.