Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach. - Mhd Saria Allahham; Tamer Khattab; Amr Mohamed 001 (ICIoT, 2020)

Energy-Efficient Device Assignment and Task Allocation in Multi-Orchestrator Mobile Edge Learning. - Mhd Saria Allahham; Sameh Sorour; Amr Mohamed 001; Aiman Erbad; Mohsen Guizani (GLOBECOM, 2021)

Patient-Driven Network Selection in multi-RAT Health Systems Using Deep Reinforcement Learning. - Heba D. M. Dawoud; Mhd Saria Allahham; Alaa Awad Abdellatif; Amr Mohamed 001; Aiman Erbad; Mohsen Guizani (GLOBECOM, 2021)

ONSRA: an Optimal Network Selection and Resource Allocation Framework in multi-RAT Systems. - Alaa Awad Abdellatif; Mhd Saria Allahham; Amr Mohamed 001; Aiman Erbad; Mohsen Guizani (ICC, 2021)

B5G: Predictive Container Auto-Scaling for Cellular Evolved Packet Core. - Yahuza Bello; Mhd Saria Allahham; Ahmed Refaey; Aiman Erbad; Amr Mohamed 001; Nabil Abdennadher (ICC Workshops, 2021)

B5G: Predictive Container Auto-Scaling for Cellular Evolved Packet Core. - Yahuza Bello; Alaa Awad Abdellatif; Mhd Saria Allahham; Ahmed Refaey Hussein; Aiman Erbad; Amr Mohamed 001; Mohsen Guizani (IEEE Access, 2021)

Energy-Efficient Multi-Orchestrator Mobile Edge Learning. - Mhd Saria Allahham; Sameh Sorour; Amr Mohamed 001; Aiman Erbad; Mohsen Guizani (CoRR, 2021)

Motivating Learners in Multi-Orchestrator Mobile Edge Learning: A Stackelberg Game Approach. - Mhd Saria Allahham; Sameh Sorour; Amr Mohamed 001; Aiman Erbad; Mohsen Guizani (CoRR, 2021)

I-SEE: Intelligent, Secure, and Energy-Efficient Techniques for Medical Data Transmission Using Deep Reinforcement Learning. - Mhd Saria Allahham; Alaa Awad Abdellatif; Amr Mohamed 001; Aiman Erbad; Elias Yaacoub; Mohsen Guizani (IEEE Internet Things J., 2021)

On the Modeling of Reliability in Extreme Edge Computing Systems. - Mhd Saria Allahham; Amr Mohamed 001; Aiman Erbad; Hossam S. Hassanein (ICCSPA, 2022)

RL-Assisted Energy-Aware User-Edge Association for IoT-based Hierarchical Federated Learning. - Hassan Saadat; Mhd Saria Allahham; Alaa Awad Abdellatif; Aiman Erbad; Amr Mohamed 001 (IWCMC, 2022)

Incentive-based Resource Allocation for Mobile Edge Learning. - Mhd Saria Allahham; Amr Mohamed 001; Hossam S. Hassanein (LCN, 2022)

Multi-Agent Reinforcement Learning for Network Selection and Resource Allocation in Heterogeneous Multi-RAT Networks. - Mhd Saria Allahham; Alaa Awad Abdellatif; Naram Mhaisen; Amr Mohamed 001; Aiman Erbad; Mohsen Guizani (IEEE Trans. Cogn. Commun. Netw., 2022)

On Designing Smart Agents for Service Provisioning in Blockchain-Powered Systems. - Naram Mhaisen; Mhd Saria Allahham; Amr Mohamed 001; Aiman Erbad; Mohsen Guizani (IEEE Trans. Netw. Sci. Eng., 2022)

Reliable Federated Learning for Age Sensitive Mobile Edge Computing Systems. - Alaa Awad Abdellatif; Mhd Saria Allahham; Noor Khial; Amr Mohamed 001; Aiman Erbad; Khaled B. Shaban (ICC, 2023)

Zero Touch Realization of Pervasive Artificial Intelligence as a Service in 6G Networks. - Emna Baccour; Mhd Saria Allahham; Aiman Erbad; Amr Mohamed 001; Ahmed Refaey Hussein; Mounir Hamdi (IEEE Commun. Mag., 2023)

Reliable Federated Learning with Auction-Based Incentives at the Extreme Edge. - Mhd Saria Allahham; Salimur Choudhury; Hossam S. Hassanein (GLOBECOM, 2024)

Quantifying the Impact of Incentives on Service Availability at the Extreme Edge. - Sherif B. Azmy; Mhd Saria Allahham; Nizar Zorba; Hossam S. Hassanein (GLOBECOM, 2024)