Mr. Mostafa Gamal, is a dedicated researcher and academic specializing in artificial intelligence, machine learning, and natural language processing, with a particular focus on text summarization and semantic graph-based models. His research explores the integration of deep learning, swarm intelligence, and optimization algorithms to enhance automated summarization and intelligent decision-making systems. He has contributed to several high-impact journals, including IEEE Access, Results in Engineering, Discover Cities, and the International Journal of Data Science and Analytics, covering areas such as transformer architectures, reinforcement learning, and graph neural networks. Mr. Gamal’s work advances the field of AI through the development of novel, explainable, and efficient models for NLP applications and autonomous systems. Beyond research, he is actively involved in academic teaching and professional training, fostering AI literacy through programs with the Egyptian Russian University, Huawei Academy, and the Digital Egypt Cubs Initiative. His technical expertise spans TensorFlow, PyTorch, and Keras, alongside proficiency in Python and data analytics frameworks. With a strong foundation in applied AI, he bridges theoretical research with practical implementation, contributing to the development of intelligent systems that address real-world challenges. His scholarly and instructional activities reflect a commitment to advancing artificial intelligence education and applied innovation in computational sciences.
Profiles: Scopus | Orcid | Google Scholar
Featured Publications
Abdul Salam, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025, December). GRAYSUM: Gray Wolf optimized multi-level semantic graph summarization. Results in Engineering, (2025), 107275.
Abdul Salam, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025, October). Abstractive text summarization using deep learning models: A survey. International Journal of Data Science and Analytics.
Gamal, M., & Ibrahim, O. A. (2025, October 24). Graph neural networks for real-time optimization of autonomous urban transit systems. Discover Cities.
Gamal, M. M., Abdul Salam, M., Sweidan, S., & Hamed, H. F. A. (2025, May 1). ACOSUM: Ant colony optimized multi-level semantic graph summarization. International Journal of Applied Intelligent Computing and Informatics.
Abdul Salam, M., Aldawsari, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2024). Improving Arabic text summarization using advanced pre-trained models. Journal of Southwest Jiaotong University, 59(3), Article 5.