🎉 Our recent paper entitled ``BLEND: Balancing Personalization vs. Generalization in Federated Vision–Language Models'' has been accepted at NeurIPS 2026
P. Abdisarabshali, et al, “BLEND: Balancing Personalization vs. Generalization in Federated Vision–Language Models”, Neural Information Processing Systems (NeurIPS) 2026.
P. Abdisarabshali, et al, “Dynamic D2D-assisted federated learning over O-RAN: Performance analysis, MAC scheduler, and asymmetric user selection”, IEEE Transactions on Networking, 2025.
_ , P. Abdisarabshali, et al, “Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions”, IEEE Transactions on Artificial Intelligence, 2025.
P. Abdisarabshali, et al, “Decomposition theory meets reliability analysis: Processing of computation-intensive dependent tasks over vehicular clouds with dynamic resources”, IEEE Transactions on Networking, 2023.
P. Abdisarabshali, et al, “Fine-Tuning Federated Foundation Models over Resource-Constrained Wireless Networks: A Generalization–Personalization Balancing Perspective”, IEEE Transactions on Wireless Communication, 2026, Submission.
_ , P. Abdisarabshali, et al, “Graph Theory Meets Federated Learning over Satellite Constellations: Spanning Aggregations, Network Formation, and Performance Optimization”, IEEE Transactions on Networking, 2025, Submission.
P. Abdisarabshali, et al, “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 Communication Magazine, 2026.
P. Abdisarabshali, et al, “Elastic Federated Learning over Open Radio Access Network (O-RAN) for Concurrent Execution of Multiple Distributed Learning Tasks”, IEEE IOT Magazine, 2025.
_ , P. Abdisarabshali, et al, “From Federated Learning to X-Learning: Breaking the Barriers of Decentrality in Distributed Machine Learning over Heterogeneous Fog/Edge Networks”, NPJ Wireless Technology, 2026.
_ , P. Abdisarabshali, et al, “Multi-Modal Multi-Task (M3T) Federated Foundation Models for Embodied AI: Potentials and Challenges for Edge Integration”, IEEE IOT Magazine, 2025.
_ , P. Abdisarabshali, et al, “Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR”, NPJ Wireless Technology, 2025.