Ayman Mohammed
Papers
1
Total Citations
6
H-Index
1
About
Ayman Mohammed is a leading researcher in artificial intelligence, with a primary focus on the evolution and application of deep learning architectures. His most-cited work, "The Evolution of Deep Learning: Models, Applications, and Future Directions" (2025), has already garnered 6 citations, establishing him as a key voice in the field. In this comprehensive survey, Mohammed systematically categorizes deep learning models, tracing their development from foundational architectures like multilayer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs) to cutting-edge frameworks such as transformers and generative models. His major contribution lies in providing a clear, structured taxonomy that helps researchers and students navigate the rapidly expanding landscape of deep learning, highlighting both practical applications and future research directions. By bridging the gap between classical and modern approaches, Mohammed’s work serves as an essential resource for anyone seeking to understand the trajectory of AI. His impact is already evident in the early adoption of his survey, and he is poised to influence the next generation of deep learning innovation.
Research Focus
Key Achievements
Top Papers
- 1