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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

S. Hassan

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4 papers indexed here

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Open access Oct 2026

A Catboost-Based Machine Learning Approach for Fault Detection in VSC-Based Multi-Terminal HVDC Grid

The proposed framework offers a data-driven approach for HVDC protection that balances the requirements of relay security and dependability and demonstrates generalization across measurement noise and provides interpretability through feature importance analysis.

Kshitij Niraula, Manilka Jayasooriya, M. N. Iqbal et al. · 0 citations
#graph neural networks Review Open access Sep 2026

AI-Driven Intrusion Detection for Vehicular Networks: A Comprehensive Survey of Techniques, Datasets, Deployment Architectures, and Future Directions

Intelligent transportation systems (ITSs), Vehicle-to-Everything (V2X) communication and autonomous driving technologies have brought about significant changes in the modern vehicular network. At the same time, the cyber-attack surface has grown, leading to new and existing advanced security threats for Vehicular Ad ho...

S. Hassan, Sadia Din, M. I. Mohmand · 0 citations
#federated learning Open access Sep 2026

FedCareX: Trust-Aware Federated Transformer for Wearable IoT Seizure Prediction

Behind-the-ear electroencephalography (EEG) can now be recorded continuously outside hospital, but forecasting the preictal state is hard in a distributed deployment: raw traces cannot leave the clinical site, the wearable montage is chosen per patient, and part of the labelling comes from automated annotators rather t...

Fahad Ali, Muhammad Shadab Alam Hashmi, M. I. Mohmand et al. · 0 citations
Open access Jul 2026

CAGE-QMol: A Constraint-Aware Quantum-Inspired Optimization Framework for Brain-Penetrant Multi-Target Alzheimer’s Drug Discovery

A mathematically grounded penalty selection rule for constrained drug-discovery QUBOs, a single end-to-end pipeline from raw public data to ranked, 3D-embedded leads, and reproducible head-to-head benchmarks between classical, quantum-inspired, and QAOA-simulated optimizers on a real Alzheimer’s task are contributed.

M. Arshad, David Q. Liu, Muhammad Bilal Sarwar et al. · 0 citations

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