Payam Abdisarabshali

14 papers Journal 14
YearRankTypeTitle / Venue / Authors
2026 J jnl
Dynamic D2D-Assisted Federated Learning Over O-RAN: Performance Analysis, MAC Scheduler, and Asymmetric User Selection.
IEEE Trans. Netw.
Payam Abdisarabshali, Kwang Taik Kim, Michael Langberg, Weifeng Su, Seyyedali Hosseinalipour
2026 J jnl
Elastic Federated Learning Over Open Radio Access Network (O-RAN) for Concurrent Execution of Multiple Distributed Learning Tasks.
IEEE Internet Things Mag.
Payam Abdisarabshali, Nicholas Accurso, Filippo Malandra, Weifeng Su, Seyyedali Hosseinalipour
2026 J jnl
Hierarchical Federated Foundation Models over Wireless Networks for Multi-Modal Multi-Task Intelligence: Integration of Edge Learning with D2D/P2P-Enabled Fog Learning Architectures.
IEEE Commun. Mag.
Payam Abdisarabshali, Fardis Nadimi, Kasra Borazjani, Naji Khosravan, Minghui Liwang, Wei Ni, Dusit Niyato, Michael Langberg, Seyyedali Hosseinalipour
2026 J jnl
Multi-Modal Multi-Task (M3T) Federated Foundation Models for Embodied AI: Potentials and Challenges for Edge Integration.
IEEE Internet Things Mag.
Kasra Borazjani, Payam Abdisarabshali, Fardis Nadimi, Naji Khosravan, Minghui Liwang, Xianbin Wang, Yiguang Hong, Seyyedali Hosseinalipour
2025 J jnl
From Federated Learning to X-Learning: Breaking the Barriers of Decentrality Through Random Walks.
CoRR
Allan Salihovic, Payam Abdisarabshali, Michael Langberg, Seyyedali Hosseinalipour
2025 J jnl
Graph Theory Meets Federated Learning over Satellite Constellations: Spanning Aggregations, Network Formation, and Performance Optimization.
CoRR
Fardis Nadimi, Payam Abdisarabshali, Jacob Chakareski, Nicholas Mastronarde, Seyyedali Hosseinalipour
2025 J jnl
Hierarchical Federated Foundation Models over Wireless Networks for Multi-Modal Multi-Task Intelligence: Integration of Edge Learning with D2D/P2P-Enabled Fog Learning Architectures.
CoRR
Payam Abdisarabshali, Fardis Nadimi, Kasra Borazjani, Naji Khosravan, Minghui Liwang, Wei Ni, Dusit Niyato, Michael Langberg, Seyyedali Hosseinalipour
2025 J jnl
Multi-Modal Multi-Task (M3T) Federated Foundation Models for Embodied AI: Potentials and Challenges for Edge Integration.
CoRR
Kasra Borazjani, Payam Abdisarabshali, Fardis Nadimi, Naji Khosravan, Minghui Liwang, Xianbin Wang, Yiguang Hong, Seyyedali Hosseinalipour
2025 J jnl
Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR.
CoRR
Fardis Nadimi, Payam Abdisarabshali, Kasra Borazjani, Jacob Chakareski, Seyyedali Hosseinalipour
2025 J jnl
Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions.
CoRR
Kasra Borazjani, Payam Abdisarabshali, Naji Khosravan, Seyyedali Hosseinalipour
2024 J jnl
Decomposition Theory Meets Reliability Analysis: Processing of Computation-Intensive Dependent Tasks Over Vehicular Clouds With Dynamic Resources.
IEEE/ACM Trans. Netw.
Payam Abdisarabshali, Minghui Liwang, Amir Rajabzadeh, Mahmood Ahmadi, Seyyedali Hosseinalipour
2024 J jnl
Dynamic D2D-Assisted Federated Learning over O-RAN: Performance Analysis, MAC Scheduler, and Asymmetric User Selection.
CoRR
Payam Abdisarabshali, Kwang Taik Kim, Michael Langberg, Weifeng Su, Seyyedali Hosseinalipour
2023 J jnl
Synergies Between Federated Learning and O-RAN: Towards an Elastic Virtualized Architecture for Multiple Distributed Machine Learning Services.
CoRR
Payam Abdisarabshali, Nicholas Accurso, Filippo Malandra, Weifeng Su, Seyyedali Hosseinalipour
2022 J jnl
Decomposition Theory Meets Reliability Analysis: Processing of Computation-Intensive Dependent Tasks over Vehicular Clouds with Dynamic Resources.
CoRR
Payam Abdisarabshali, Seyyedali Hosseinalipour, Minghui Liwang, Amir Rajabzadeh, Mahmood Ahmadi