*Authors contributed equally

Members of the SAYED Systems Group are indicated in boldface

2023

Ahmed M. Abdelmoniem, B Bensaou. Enhancing TCP via Hysteresis Switching: Theoretical Analysis and Empirical Evaluation. IEEE/ACM Transactions on Networking (2023). link Paper

Ahmed M. Abdelmoniem, CY Ho, P Papageorgiou, M Canini. A Comprehensive Empirical Study of Heterogeneity in Federated Learning. IEEE Internet of Things Journal (2023). Link Paper

Ahmed M. Abdelmoniem, Y M. Abdelmoniem, A Elzanaty A2FL: Availability-Aware Selection for Machine Learning on Clients with Federated Big Data. IEEE ICC (2023). Preprint Paper Conference Paper

E Bragion, H Akter, M Kumar, M Xu, Ahmed M. Abdelmoniem, SS Gill. Fortaleza: The emergence of a network hub. Elsevier Internet of Things and Cyber-Physical Systems 3, 272-279 (2023). link

Ahmed M. Abdelmoniem, Atal N. Sahu, Marco Canini, Suhaib Fahmy. REFL: Resource Efficient Federated Learning. ACM EuroSys (2023) link ArXiv Paper

2022

Ahmed M. Abdelmoniem. Towards Efficient and Practical Federated Learning. CrossFL-MLSys (2022) Abstract Poster

Amna Arouj, Ahmed M. Abdelmoniem. Towards Energy-Aware Federated Learning on Battery-Powered Clients,. To Appear in ACM FedEdge-MobiCom (2022) ArXiv

Ahmed M. Abdelmoniem, Chen-Yu Ho, Pantelis Papageorgiou, and Marco Canini. Empirical analysis of federated learning in heterogeneous environments. ACM EuroMLSys-EuroSys. Paper ArXiv