activity
20242026
collaborators

8 papers

eess.SP2026

FLAME: A Federated Learning Approach for Multi-Modal RF Fingerprinting

Kasra Borazjani, Kiarash Kianfar, Seyyedali Hosseinalipour +1

Authorization systems are increasingly relying on processing radio frequency (RF) waveforms at receivers to fingerprint (i.e., determine the identity of) the corresponding transmit…

cs.LG2026

Federated Foundation Models over Vehicular Networks

Kasra Borazjani, Fardis Nadimi, Payam Abdisarabshali +5

This paper presents a forward-looking vision for integrating the emerging multi-modal multi-task federated foundation models (M3T FedFMs) into vehicular networks, with the goal of…

cs.CV2026

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 +1

Federated Learning (FL) has emerged as one of the prominent paradigms for distributed machine learning (ML). However, it is well-established that its performance can degrade signif…

cs.LG2025

Bringing Multi-Modal Multi-Task Federated Foundation Models to Education Domain: Prospects and Challenges

Kasra Borazjani, Naji Khosravan, Rajeev Sahay +2

Multi-modal multi-task (M3T) foundation models (FMs) have recently shown transformative potential in artificial intelligence, with emerging applications in education. However, thei…

cs.AI2025

Multi-Modal Multi-Task (M3T) Federated Foundation Models for Embodied AI: Potentials and Challenges for Edge Integration

Kasra Borazjani, Payam Abdisarabshali, Fardis Nadimi +5

As embodied AI systems become increasingly multi-modal, personalized, and interactive, they must learn effectively from diverse sensory inputs, adapt continually to user preference…

cs.LG2025

Hierarchical Federated Foundation Models over Wireless Networks for Multi-Modal Multi-Task Intelligence: Integration of Edge Learning with D2D/P2P-Enabled Fog Learning Architectures

Payam Abdisarabshali, Fardis Nadimi, Kasra Borazjani +6

The rise of foundation models (FMs) has reshaped the landscape of machine learning. As these models continued to grow, leveraging geo-distributed data from wireless devices has bec…