1 citations · 1 across the 10 of their papers we have counts for
16 papers
Catastrophic Forgetting in Sequential Thermal Anti-UAV Detection: The Role of Scale-Conditioned Gradient Imbalance
Khac Duc Giang Nguyen, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag
Counter-UAV systems based on thermal infrared detection must stay accurate as operational datasets evolve, yet sequential fine-tuning causes catastrophic forgetting of prior tasks,…
Predicting Delayed Train Trajectories on the Dutch Railway Network: Explainable AI Evaluation of Topological, Operational and Weather Features with Tree Based Ensemble Methods
Jia Long Bao, Ali Mohammed Mansoor Alsahag, Seyed Sahand Mohammadi Ziabari
The reliable prediction of passenger train delays is a critical component of railway management. While contemporary research frequently attempts to maximize absolute accuracy by de…
Evaluating the Robustness of Anti-UAV Detection under Controlled Fog Degradation: Fog-Aware Training and Clear-Sky Tradeoff
Gur Levy Birkental, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag
Vision-based anti-UAV systems must function in poor visibility, yet most benchmarks use only clear-sky footage, and previous robustness studies treat adverse weather as a simple pr…
SCM-based Fairness and Faithful Explainability for Legal Document Classification
Yasmina El Kacemi, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag
Transformer models such as LegalBERT are increasingly used in legal decision support, raising concerns about both fairness and the transparency of model explanations. These propert…
Integrating Fairness and Explainability in a Multiple Instance Reinforcement Learning System
Bente Hinkenhuis, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag
Predicting student performance from educational interaction data requires models that are both accurate and sufficiently transparent to support meaningful intervention, while demog…
Fairness-Aware Multimodal Transformer Modeling for Real-Time Student Attention Estimation
Christoforos Fragkiadakis, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag
Automated student-attention estimation can support learning analytics, but aggregate predictive metrics can conceal demographic disparities. This study evaluates fairness-aware mul…
Evidential Deep Learning for Multi-Modal Anti-UAV Detection
Dmitry Golovchits, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag
Anti-UAV systems increasingly fuse multiple sensors, yet their detection heads provide no per-modality reliability signal. This study evaluates whether evidential deep learning (ED…
Uncertainty-Aware Multimodal Anti-UAV Detection via Evidential Fusion and Conflict-Discounted Belief Aggregation
Sharanda Suttorp, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansour Alsahag
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 R…
Causally Disentangled Contrastive Learning for Multilingual Speaker Embeddings
Mariëtte Olijslager, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag
Self-supervised speaker embeddings are widely used in speaker verification systems, but prior work has shown that they often encode sensitive demographic attributes, raising fairne…
Hybrid Vision Transformer_GAN Attribute Neutralizer for Mitigating Bias in Chest X_Ray Diagnosis
Jobeal Solomon, Ali Mohammed Mansoor Alsahag, Seyed Sahand Mohammadi Ziabari
Bias in chest X-ray classifiers frequently stems from sex- and age-related shortcuts, leading to systematic underdiagnosis of minority subgroups. Previous pixel-space attribute neu…
Assessing the quality and coherence of word embeddings after SCM-based intersectional bias mitigation
Eren Kocadag, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag
Static word embeddings often absorb social biases from the text they learn from, and those biases can quietly shape downstream systems. Prior work that uses the Stereotype Content…
Cross-Language Speaker Attribute Prediction Using MIL and RL
Sunny Shu, Seyed Sahand Mohammadi Ziabari, Ali Mohammed Mansoor Alsahag
We study multilingual speaker attribute prediction under linguistic variation, domain mismatch, and data imbalance across languages. We propose RLMIL-DAT, a multilingual extension…
Fairness Metric Design Exploration in Multi-Domain Moral Sentiment Classification using Transformer-Based Models
Battemuulen Naranbat, Seyed Sahand Mohammadi Ziabari, Yousuf Nasser Al Husaini +1
Ensuring fairness in natural language processing for moral sentiment classification is challenging, particularly under cross-domain shifts where transformer models are increasingly…
Predicting Delayed Trajectories Using Network Features: A Study on the Dutch Railway Network
Merel Kampere, Ali Mohammed Mansoor Alsahag
The Dutch railway network is one of the busiest in the world, with delays being a prominent concern for the principal passenger railway operator NS. This research addresses a gap i…
Time series classification of satellite data using LSTM networks: an approach for predicting leaf-fall to minimize railroad traffic disruption
Hein de Wilde, Ali Mohammed Mansoor Alsahag, Pierre Blanchet
Railroad traffic disruption as a result of leaf-fall cost the UK rail industry over 300 million per year and measures to mitigate such disruptions are employed on a large scale, wi…
A Framework for Multi-View Multiple Object Tracking using Single-View Multi-Object Trackers on Fish Data
Chaim Chai Elchik, Fatemeh Karimi Nejadasl, Seyed Sahand Mohammadi Ziabari +1
Multi-object tracking (MOT) in computer vision has made significant advancements, yet tracking small fish in underwater environments presents unique challenges due to complex 3D mo…