collaborators

15 papers

cs.NI2026

Out-of-Distribution Detection in Wireless Multimodal Foundation Models for 6G ISAC

Mohammad Farzanullah, Akram Bin Sediq, Ali Afana +1

The integration of Foundation Models (FMs), such as the Wireless Multimodal Foundation Model (WMFM), into 6G networks provides a unified framework for Integrated Sensing and Commun…

eess.SP2026

Dual-Transformer Aided Hierarchical Deep Reinforcement Learning for Robust RIS-Assisted Near-Field Communications

Mohammad Ghassemi, Han Zhang, Ali Afana +2

The deployment of extremely large aperture arrays (ELAAs) in sixth-generation (6G) networks is expected to shift communications into the near-field regime, where spherical-wave pro…

cs.NI2026

Chain-of-Thought Reasoning Enhances In-Context Learning for LLM-Based Mobile Traffic Prediction

MohammadMahdi Ghadaksaz, Mohammad Farzanullah, Akram Bin Sediq +2

Accurate short-term mobile traffic prediction is important for proactive resource allocation and low-latency network management in fifth generation (5G) and sixth generation (6G).…

cs.LG2026

Regularized Top-: A Bayesian Framework for Gradient Sparsification

Ali Bereyhi, Ben Liang, Gary Boudreau +1

Error accumulation is effective for gradient sparsification in distributed settings: initially-unselected gradient entries are eventually selected as their accumulated error exceed…

eess.SP2026

Foundation Model-Aided Hierarchical Deep Reinforcement Learning for Blockage-Aware Link in RIS-Assisted Networks

Mohammad Ghassemi, Han Zhang, Ali Afana +2

Reconfigurable intelligent surface (RIS) technology has the potential to significantly enhance the spectral efficiency (SE) of 6G wireless networks. However, practical deployment r…

cs.NI2026

Multi-Modal Data-Enhanced Foundation Models for Prediction and Control in Wireless Networks: A Survey

Han Zhang, Mohammad Farzanullah, Mohammad Ghassemi +3

Foundation models (FMs) are recognized as a transformative breakthrough that has started to reshape the future of artificial intelligence (AI) across both academia and industry. Th…