Mahmoud Ragab
Research areas: Computer Science · Artificial Intelligence · Network Security and Intrusion Detection · AI in cancer detection · Advanced Neural Network Applications
0000-0002-4427-0016
About
Mahmoud Ragab obtained his Ph.D. degree from the Faculty of Mathematics and Natural Sciences at the Christian-Albrechts-University in Kiel (CAU), Schleswig-Holstein, Germany. He received his B.SC. degree in Statistics Computer Science from Mansoura University in Mansoura, Egypt. He is a professor of data science at the Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University in Jeddah, Saudi Arabia and the Mathematics Department, Faculty of Science, Al Azhar University in Cairo, Egypt. He worked in different research groups at various universities such as the Combinatorial Optimization and Graph Algorithms Group (COGA), Faculty of Mathematics and Natural Sciences, Berlin University of Technology in Berlin, Germany; Faculty of Informatics and Computer Science at the British University in Egypt BUE; Integrated Communication Systems Group at Ilmenau University of Technology TU Ilmenau, in Thüringen, Germany. Now he is a researcher at various centers such as: University of Oxford Centre for Artificial Intelligence in Precision medicines; Center of Research Excellence in Artificial Intelligence and Data Science; Center of Excellence in Smart Environment Research at King Abdulaziz University, Jeddah, Saudi Arabia. He has publishedmany papers in refereed high-impact journals, books, and patents. His research focuses on: AI, Deep learning, Optimization, Mathematical Modeling, Data Science, Neural Networks, Time series analysis, and decision support systems.
Employment
Employment history is unavailable.
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (235)
- An attention-driven recurrent network and vision transformer-based assistive model for disability-oriented human activity recognition Save
- Explainable attention-guided deep learning for physiological signal processing in body area networks Save
- Smartphone based clinical decision support system for early detection of neonatal jaundice using artificial intelligence with temporal convolutional network Save
- Integrating whole-brain and masked-lesion CNN pipelines via multistage soft voting for enhanced three-class MRI tumor classification Save
- Mathematically structured quantum time-series analytics with dual-stream convolutional recurrent network for advanced smart grid fault detection Save
- Explainable artificial intelligence with fusion of feature engineering on oral disease diagnosis in dentistry using biomedical images Save
- Advances in electrocardiogram signal analytics for person identification using fine-grained fusion-driven deep representation learning under arrhythmic conditions Save
- Artificial intelligence with deep convolutional neural network-based clinical decision-making on kidney Oncology using multimodal imaging Save
- Deep neural architecture empowered by explainable artificial intelligence for accurate and early diagnosis of gynaecological cancer using medical images Save
- Explainable artificial intelligence of things integrated spatio-temporal feature modeling for traffic congestion framework on intelligent urban mobility system Save
- Explainable multi-backbone deep feature fusion based wheelchair detection with disability-aware accessibility monitoring in smart urban environments Save
- Harnessing Educational Predictive Analytics: Empowering Data-Driven Insights for Academic Performance Save
- Intelligent underwater mine detection using multi-backbone feature fusion with temporal attention-gated unit on side-scan sonar imaging Save
- Interpretable Attention-Guided Graph Convolutional Networks for Fetal Anatomical Plane Classification using Ultrasound Images Save
- Modeling of automated renal lithiasis identification using feature fusion with attention-based deep learning model on axial computed tomography images Save
- Modelling of enhanced predictive analytics and decision-making approach using recurrent autoencoder with attribute subset reduction for students’ academic performance Save
- The impact of artificial intelligence with multi-head self-attention based deep learning model for students' academic performance monitoring Save
- Medical Feature Extraction From Clinical Examination Notes: Development and Evaluation of a Two-Phase Large Language Model Framework Save
- Smart mobile application for real-time monitoring and prediction of pilgrim crowd activities in Hajj and Umrah using wearable sensors Save
- Integrating convolutional stacked long short-term memory with bio-inspired algorithm for secure unmanned aerial vehicle communication in SDN environment Save