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).