Optimal User-Edge Assignment in Hierarchical Federated Learning

Jan 1, 2021·
Naram Mhaisen
Naram Mhaisen
,
Alaa Awad Abdellatif
,
Amr Mohamed
,
Aiman Erbad
,
Mohsen Guizani
Abstract
We formulate and solve the user-to-edge assignment problem in hierarchical federated learning to balance training accuracy and communication cost.
Type
Publication
IEEE Transactions on Network Science and Engineering
publications
Federated Learning Optimization
Naram Mhaisen
Authors
Naram Mhaisen
Postdoctoral Researcher

Naram is a Postdoctoral Researcher with the Networked Systems Group at the Faculty of Electrical Engineering, Mathematics, and Computer Science, TU Delft, The Netherlands. His research focuses on online learning techniques with applications in resource management across communication systems.

He received the B.Sc. degree in Computer Engineering from Qatar University in 2017 with the Order of Excellence award, and the M.Sc. degree with Distinction in Computing from Qatar University in 2020, supervised by Prof. Mohsen Guizani. He completed his Ph.D. at TU Delft in 2025, supervised by Dr. George Iosifidis, with a thesis on Optimistic Learning with Applications to Caching Networks.

His work has been recognized by the Microsoft Imagine Cup award (2017) and a NEC Europe Research Fellowship (2022).