Author

S. S. M. Ziabari

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Preprint Aug 2026

Uncertainty-Aware Multimodal Anti-UAV Detection via Evidential Fusion and Conflict-Discounted Belief Aggregation

Anti-UAV perception systems must remain reliable when sensor streams degrade under occlusion, fast motion, or modality-specific failure. Existing multimodal anti-UAV systems fuse RGB and thermal streams deterministically, without modeling predictive uncertainty, and cannot express doubt when streams disagree. Evidentia...

Sharanda Suttorp, S. S. M. Ziabari, A. M. M. Alsahag · 2 citations

#natural language process... Preprint Sep 2026

SCM-based Fairness and Faithful Explainability for Legal Document Classification

Transformer models such as LegalBERT are increasingly used in legal decision support, raising concerns about both fairness and the transparency of model explanations. These properties are usually evaluated separately, leaving open whether a debiasing intervention that changes fairness also changes how faithfully explan...

Yasmina El Kacemi, S. S. M. Ziabari, A. M. Alsahag · 0 citations

#machine learning Preprint Sep 2026

Integrating Fairness and Explainability in a Multiple Instance Reinforcement Learning System

Predicting student performance from educational interaction data requires models that are both accurate and sufficiently transparent to support meaningful intervention, while demographic information introduces an additional risk of unfair predictions. This study investigates a multi-objective framework that combines re...

Bente Hinkenhuis, S. S. M. Ziabari, A. M. Alsahag · 0 citations

#machine learning Preprint Sep 2026

Predicting Delayed Train Trajectories on the Dutch Railway Network: Explainable AI Evaluation of Topological, Operational and Weather Features with Tree Based Ensemble Methods

It is demonstrated that richer feature sets alone are insufficient to resolve long-term forecasting constraints, underscoring the necessity to transition toward dynamic, season-aware architectures anchored by absolute operational boundaries.

Jia-Long Bao, A. M. Alsahag, S. S. M. Ziabari · 0 citations

Preprint Sep 2026

Evidential Deep Learning for Multi-Modal Anti-UAV Detection

Empirical deep learning heads, Dempster-Shafer evidence fusion, and uncertainty-driven temporal sensor gating improve anti-UAV detection through a controlled ablation on three benchmarks: thermal tracking, RGB-audio-RF classification, and RGB-IR tracking.

Dmitry Golovchits, S. S. M. Ziabari, A. M. M. Alsahag · 0 citations