Dr. Maher Alrahhal | Security | Best Researcher Award

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Dr. Maher Alrahhal | Security | Best Researcher Award

Postdoctoral, University of Sharjah, United Arab Emirates

Dr. Maher Abdul Moein Alrahhal is a Postdoctoral Research Associate at the Research Institute of Science and Engineering, University of Sharjah, UAE, and a Postdoctoral Fellow at Amity University Dubai, UAE. He holds a Ph.D. in Computer Science and Engineering from Jawaharlal Nehru Technological University (JNTU), Hyderabad, India, specializing in Artificial Intelligence, Big Data, and Data Analysis. With a solid background in computer science and engineering, Dr. Alrahhal has made significant contributions to the fields of machine learning, image retrieval, and data mining 🌐💡.

Publication Profile

Google Scholar

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🎓Education Background

Dr. Alrahhal’s educational journey is marked by excellence, with a Ph.D. in Computer Science and Engineering from JNTU, Hyderabad, India (March 2024). He completed his Master of Technology in Computer Science and Engineering with First Division from the National Institute of Technology, Warangal, India (July 2018). He holds a Bachelor’s degree in Computer Engineering from the University of Aleppo, Syria, graduating with honors and securing the first rank in his department 🏆📚.

👨‍🏫Professional Experience

Dr. Alrahhal has a robust academic career with over five years of teaching experience at prominent institutions in Syria and India. He has served as a Teaching Assistant at the University of Aleppo, and later as a Lecturer and Assistant Supervisor at JNTU, Hyderabad. Dr. Alrahhal also led the Big Data Lab at JNTU and played a key role in mentoring seven master’s students. His postdoctoral roles involve research and teaching at the University of Sharjah and Amity University Dubai, UAE 💻📖.

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🏅Awards and Honors

Dr. Alrahhal has received several prestigious awards, including the Best Paper Award at IEMTRONICS 2025 for his work on “Hybrid CNN for Efficient Content-Based Image Retrieval Cognitive Systems” 🥇. In recognition of his outstanding achievements, he was honored with the Alan Turing Award at the International Royal Golden Award ceremony (2023). Other notable accolades include the University Excellence Distinction for first-ranking in 2014 and multiple Al-Basel Certificates for Excellence 🏅🎖️.

🔍 Research Focus

Dr. Alrahhal’s research focuses on Artificial Intelligence, Machine Learning, Big Data, Data Mining, and Image Retrieval. His work explores the integration of deep learning techniques with image and video processing, multimedia systems, and the application of Hadoop for scalable data analysis. His contributions aim to advance content-based image retrieval systems and the development of intelligent systems for real-world applications 📊🤖.

💡🌐Conclusion

Dr. Maher Abdul Moein Alrahhal is a dynamic researcher and academic, committed to advancing the fields of Artificial Intelligence and Data Science. With numerous published works in high-impact journals and ongoing research initiatives, he continues to shape the future of intelligent systems and multimedia applications 🌟📈.

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📚Publications

Disruptive Attacks on Artificial Neural Networks: A Systematic Review of Attack Techniques, Detection Methods, and Protection Strategies, Intelligent Systems with Applications, in press.

MapReduce model for efficient image retrieval: a Hadoop-based framework, International Journal of Information Technology (Springer, Scopus Q1).

Enhancing Image Retrieval Systems: A Comprehensive Review of Machine Learning Integration In CBIR, International Journal of Intelligent Systems and Applications in Engineering, 12(4), 4195–4214.

Integrating Machine Learning Algorithms for Robust Content-Based Image Retrieval, International Journal of Information Technology, DOI: 10.1007/s41870-024-02169-2 (Springer, Scopus Q1).

Automatic diagnosis of epileptic seizures using entropy-based features and Multimodal Deep Learning Approaches, Medical Engineering and Physics, DOI: 10.1016/j.medengphy.2024.104206, (Elsevier, Scopus Q1).

Enhancing image retrieval accuracy through multi-resolution HSV-LNP feature fusion and modified K-NN relevance feedback, International Journal of Information Technology, DOI: 10.1007/s41870-024-02000-y, (Springer, Scopus Q1).

Dr. DURGADEVI P | Network security | Best Researcher Award

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Dr. DURGADEVI P | Network security | Best Researcher Award

Assistant Professor, SRM INSTITUTE OF SCIENCE AND ENGINEERING, India

Dr. P. Durgadevi is a passionate academician and researcher in the field of Computer Science and Engineering with over 16 years of teaching and research experience. She is currently serving as an Assistant Professor (S.G.) at SRM Institute of Science and Technology, Vadapalani, Chennai. Her expertise spans across Cloud Computing, Machine Learning, Artificial Intelligence, and Swarm Optimization Algorithms. She has made significant contributions to academia by mentoring research scholars, publishing high-impact papers, and actively participating in professional organizations. Her commitment to excellence has earned her multiple awards and recognitions, establishing her as a distinguished educator and researcher. 📚✨

Publication Profile

Education 🎓

Dr. Durgadevi holds a Ph.D. in Information and Communication Engineering from Anna University, Chennai (2019). She completed her M.E. in Computer Science and Engineering from Arunai Engineering College, Tiruvannamalai with 84% (2009) and her B.Tech in Information Technology from Kamban Engineering College, Tiruvannamalai with 82% (2005). Her strong academic background has laid the foundation for her impactful research in computing and optimization techniques. 🎯

Experience 👩‍🏫

With a career spanning over 16 years, Dr. Durgadevi has held various prestigious teaching positions. She has been an Assistant Professor (S.G.) at SRM Institute of Science and Technology since October 2023 and previously served as an Assistant Professor (Sr.G.) at the same institution (2020-2023). She has also worked as an Associate Professor at Vel Tech Dr. Rangarajan Dr. Sagunthala R&D Institute of Science and Technology and as an Assistant Professor at RMK College of Engineering and Technology and Arunai Engineering College. Her extensive experience in teaching, research supervision, and academic mentoring has contributed significantly to the growth of students and young researchers. 🏆

Awards and Honors 🏅

Dr. Durgadevi has received numerous accolades for her contributions to academia and research. She was honored with the “Best Teaching Faculty” award by Dr. Abdul Kalam Education Trust (2019) and the “Young Woman in Engineering” award by Venus Foundation (2018). She has been recognized as a Top Performing Mentor by NPTEL, earning multiple Elite and Silver Certifications for excellence in courses like Big Data Computing and The Joy of Computing in Python. She has also received Best Paper Awards at renowned international conferences such as ICCAI 2021 and ICOICI 2022. Her commitment to academic excellence is further demonstrated by her lifetime memberships in prestigious organizations like ISTE, CSI, IAENG, and CSTA. 🏆🌟

Research Focus 🔬

Dr. Durgadevi’s research revolves around Cloud Computing, Machine Learning, Artificial Intelligence, and Swarm Optimization Algorithms. Her Ph.D. work focused on “An Optimal Resource Discovery and Allocation in Cloud Using Hybrid Swarm Optimization Algorithms”, aiming to enhance cloud resource management efficiency. She is an active research supervisor at SRM Institute of Science and Technology, guiding four research scholars and serving as a Doctoral Committee Member for Anna University scholars. Her work emphasizes metaheuristic optimization, network security, and intelligent computing, contributing to the development of robust and scalable computing solutions. 🚀

Conclusion 🌍

Dr. P. Durgadevi is an accomplished researcher, educator, and mentor, making remarkable strides in the field of Computer Science and Engineering. Her dedication to research, excellence in teaching, and active engagement in professional communities have solidified her reputation as a leading academician. With her extensive contributions to Cloud Computing, AI, and Swarm Intelligence, she continues to inspire and shape the next generation of computing professionals. 🚀🎯

Publications 📖

Optimizing network security: Weighted average ensemble of BPNN and RELM in EPRN-WPS intrusion detection

Resource Allocation in Cloud Computing using SFLA and Cuckoo Search Hybridization, International Journal of Parallel Programming, 2020 – Cited by 34

Task Scheduling using Amalgamation of Metaheuristics Swarm Optimization Algorithm and Cuckoo Search in Cloud Computing, Journal for Research, 2015 – Cited by 11

Recognition of Face Grounded on Aging Factors by Exploiting AI Techniques, Annals of the Romanian Society for Cell Biology, 2021 – Cited by

Flood Detection and Management using IoT and Correlation Analysis, Journal of Interdisciplinary Cycle Research, 2021

Comparative Analysis of Color and Texture-Based Skin Recognition Techniques, Psychology and Education Journal, 2021

Public Key Encryption with Keyword Search, International Journal of Advance Research, Ideas, and Innovations, 2021

Prediction and Control of Accident Risks Using Logistic Model Learning Technique, Solid State Technology, 2020

Bank Endorsement Classification: A Novel Content-Based Approach Using Pupil Tracking Technology, Journal of Computational and Theoretical Nanoscience, 2020

 

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.