Nordine Quadar | Cybersecurity | Best Researcher Award

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Mr. Nordine Quadar | Cybersecurity | Best Researcher Award

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.

 

 

François PERES | risk management | Best Researcher Award

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Prof. François PERES | risk management | Best Researcher Award

Head of Scientific Research Department, UTTOP – University of Toulouse, France

François Pérès is a distinguished French professor at Toulouse University, where he leads research in production engineering and risk management. He specializes in analyzing vulnerabilities and managing uncertainties in natural and technical systems. As an active figure in academic societies, he serves as Vice-Chair of IFAC TC5.1 & TC8.3 and chairs the ESRA Manufacturing Technical Committee. His leadership extends to directing the STP Chapter of SAGIP, and he is President of the CES 10 committee for the ANR. With a career rich in academic and industrial experiences, he is a key player in advancing research on the “industry of the future” 🌍📚.

Publication Profile

Google Scholar

Education

François Pérès holds a PhD in Mechanical Engineering from Bordeaux I University (1996), following his Production Engineering degree from ENIT Tarbes (1991). His academic journey also includes a Master’s Thesis from Bordeaux I University. In 2005, he earned the Accreditation for Research Supervision (HDR) from INP Toulouse 🎓⚙️.

Experience

Currently a full professor at Toulouse University (INPT–ENIT), François Pérès has a rich professional background. He began as a Design Engineer at Airbus in Toulouse and later transitioned to Renault Trucks in the UK. His academic career includes roles as an Assistant Professor at Ecole Centrale Paris and extensive PhD supervision. He also contributes significantly to international research organizations and committees, representing France globally 🌐✈️.

Research Focus

François Pérès focuses on risk assessment, decision support, and uncertainty management in both industrial and environmental systems. His recent work extends to flood event modeling and developing hybrid models using dynamic Bayesian networks. He supervises several PhD students working on complex systems, merging probabilistic tools with physical laws to address risk in various domains 🌊📊.

Awards and Honours

Throughout his career, François Pérès has garnered several prestigious roles, including serving as the President of the Scientific Evaluation Committee “Industry of the Future” for ANR. He is a valued expert for organizations such as NATO and the European Commission. His leadership in IFAC and ESRA demonstrates his significant contributions to industrial engineering and risk management 🏆🌟.

Publication Top Notes

François Pérès has published extensively, including over 40 articles in international journals and more than 100 conference papers. His work includes co-authoring books, book chapters, and patents. His notable research includes contributions to the development of Bayesian networks for risk assessment and modeling of river systems. His research papers are widely cited in leading journals 📑✨.

Multidimensional Bayesian Networks for Modelling Complex Systems, 2024, Authorea Preprints.

Numerical modelling of the evolution of a river reach with a complex morphology, 2023, Earth Surface Dynamics.

Participatory Bayesian modelling for sustainable and efficient river restoration projects, 2020, Journal of Contingencies and Crisis Management.

Data-driven model for river flood forecasting, 2020, Journal of Contingencies and Crisis Management.