Synergies Between Federated Learning and O-RAN: Towards an Elastic Virtualized Architecture for Multiple Distributed Machine Learning Services. - Payam Abdisarabshali; Nicholas Accurso; Filippo Malandra; Weifeng Su; Seyyedali Hosseinalipour (CoRR, 2023)

Dynamic D2D-Assisted Federated Learning over O-RAN: Performance Analysis, MAC Scheduler, and Asymmetric User Selection. - Payam Abdisarabshali; Kwang Taik Kim; Michael Langberg; Weifeng Su; Seyyedali Hosseinalipour (CoRR, 2024)

Decomposition Theory Meets Reliability Analysis: Processing of Computation-Intensive Dependent Tasks Over Vehicular Clouds With Dynamic Resources. - Payam Abdisarabshali; Minghui Liwang; Amir Rajabzadeh; Mahmood Ahmadi; Seyyedali Hosseinalipour (IEEE/ACM Trans. Netw., 2024)

Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions. - Kasra Borazjani; Payam Abdisarabshali; Naji Khosravan; Seyyedali Hosseinalipour (CoRR, 2025)

Multi-Modal Multi-Task (M3T) Federated Foundation Models for Embodied AI: Potentials and Challenges for Edge Integration. - Kasra Borazjani; Payam Abdisarabshali; Fardis Nadimi; Naji Khosravan; Minghui Liwang; Xianbin Wang 001; Yiguang Hong; Seyyedali Hosseinalipour (CoRR, 2025)

Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR. - Fardis Nadimi; Payam Abdisarabshali; Kasra Borazjani; Jacob Chakareski; Seyyedali Hosseinalipour (CoRR, 2025)