55 citations · 179 across the 24 of their papers we have counts for
24 papers
RINSE: Robust Target-Time Normality Estimation for Zero-Shot Graph Anomaly Detection
Taufikur Rahman Fuad, Md Abrar Jahin, Amir Hussain
Zero-shot graph anomaly detection seeks to deploy a detector trained on source graphs to unseen, unlabeled targets, yet domain shift can make source-derived notions of normality un…
ChronoSpike: An Adaptive Spiking Graph Neural Network for Dynamic Graphs
Md Abrar Jahin, Taufikur Rahman Fuad, Jay Pujara +1
Dynamic graph representation learning requires capturing both structural relations and temporal evolution, yet existing approaches face a core trade-off: attention-based methods of…
DyCAF-Net: Dynamic Class-Aware Fusion Network
Md Abrar Jahin, Shahriar Soudeep, M. F. Mridha +2
Recent advancements in object detection rely on modular architectures with multi-scale fusion and attention mechanisms. However, static fusion heuristics and class-agnostic attenti…
AdeptHEQ-FL: Adaptive Homomorphic Encryption for Federated Learning of Hybrid Classical-Quantum Models with Dynamic Layer Sparing
Md Abrar Jahin, Taufikur Rahman Fuad, M. F. Mridha +2
Federated Learning (FL) faces inherent challenges in balancing model performance, privacy preservation, and communication efficiency, especially in non-IID decentralized environmen…
Physics-Informed Graph Neural Networks for Transverse Momentum Estimation in CMS Trigger Systems
Md Abrar Jahin, Shahriar Soudeep, M. F. Mridha +2
Real-time particle transverse momentum () estimation in high-energy physics demands algorithms that are both efficient and accurate under strict hardware constraints. Static m…
Quantum-Informed Contrastive Learning with Dynamic Mixup Augmentation for Class-Imbalanced Expert Systems
Md Abrar Jahin, Adiba Abid, M. F. Mridha
Expert systems often operate in domains characterized by class-imbalanced tabular data, where detecting rare but critical instances is essential for safety and reliability. While c…
Vision Transformers for End-to-End Quark-Gluon Jet Classification from Calorimeter Images
Md Abrar Jahin, Shahriar Soudeep, Arian Rahman Aditta +3
Distinguishing between quark- and gluon-initiated jets is a critical and challenging task in high-energy physics, pivotal for improving new physics searches and precision measureme…
Soybean Disease Detection via Interpretable Hybrid CNN-GNN: Integrating MobileNetV2 and GraphSAGE with Cross-Modal Attention
Md Abrar Jahin, Soudeep Shahriar, M. F. Mridha +2
Soybean leaf disease detection is critical for agricultural productivity but faces challenges due to visually similar symptoms and limited interpretability in conventional methods.…
CAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network for Network Intrusion Detection
Md Abrar Jahin, Shahriar Soudeep, Fahmid Al Farid +4
Cybersecurity threats are growing, making network intrusion detection essential. Traditional machine learning models remain effective in resource-limited environments due to their…
Interpretable Dynamic Graph Neural Networks for Small Occluded Object Detection and Tracking
Shahriar Soudeep, Md Abrar Jahin, M. F. Mridha
The detection and tracking of small, occluded objects such as pedestrians, cyclists, and motorbikes pose significant challenges for traffic surveillance systems because of their er…
KACQ-DCNN: Uncertainty-Aware Interpretable Kolmogorov-Arnold Classical-Quantum Dual-Channel Neural Network for Heart Disease Detection
Md Abrar Jahin, Md. Akmol Masud, M. F. Mridha +2
Heart failure is a leading cause of global mortality, necessitating improved diagnostic strategies. Classical machine learning models struggle with challenges such as high-dimensio…
TriQXNet: Forecasting Dst Index from Solar Wind Data Using an Interpretable Parallel Classical-Quantum Framework with Uncertainty Quantification
Md Abrar Jahin, M. F. Mridha, Zeyar Aung +2
Geomagnetic storms, caused by solar wind energy transfer to Earth's magnetic field, can disrupt critical infrastructure like GPS, satellite communications, and power grids. The dis…
Optimizing Container Loading and Unloading through Dual-Cycling and Dockyard Rehandle Reduction Using a Hybrid Genetic Algorithm
Md. Mahfuzur Rahman, Md Abrar Jahin, Md. Saiful Islam +1
This paper addresses the NP-hard problem of optimizing container handling at ports by integrating Quay Crane Dual-Cycling (QCDC) and dockyard rehandle minimization. We realized tha…
MCDFN: Supply Chain Demand Forecasting via an Explainable Multi-Channel Data Fusion Network Model
Md Abrar Jahin, Asef Shahriar, Md Al Amin
Accurate demand forecasting is crucial for optimizing supply chain management. Traditional methods often fail to capture complex patterns from seasonal variability and special even…
A hybrid transformer and attention based recurrent neural network for robust and interpretable sentiment analysis of tweets
Md Abrar Jahin, Md Sakib Hossain Shovon, M. F. Mridha +2
Sentiment analysis is crucial for understanding public opinion and consumer behavior. Existing models face challenges with linguistic diversity, generalizability, and explainabilit…
Predicting Male Domestic Violence Using Explainable Ensemble Learning and Exploratory Data Analysis
Md Abrar Jahin, Saleh Akram Naife, Fatema Tuj Johora Lima +2
Domestic violence is commonly viewed as a gendered issue that primarily affects women, which tends to leave male victims largely overlooked. This study presents a novel, data-drive…
Ergonomic Design of Computer Laboratory Furniture: Mismatch Analysis Utilizing Anthropometric Data of University Students
Anik Kumar Saha, Md Abrar Jahin, Md. Rafiquzzaman +1
Many studies have shown how ergonomically designed furniture improves productivity and well-being. As computers have become a part of students' academic lives, they will grow furth…
Analysis of Internet of Things Implementation Barriers in the Cold Supply Chain: An Integrated ISM-MICMAC and DEMATEL Approach
Kazrin Ahmad, Md. Saiful Islam, Md Abrar Jahin +1
Integrating Internet of Things (IoT) technology inside the cold supply chain can enhance transparency, efficiency, and quality, optimizing operating procedures and increasing produ…
AI in Supply Chain Risk Assessment: A Systematic Literature Review and Bibliometric Analysis
Md Abrar Jahin, Saleh Akram Naife, Anik Kumar Saha +1
Supply chain risk assessment (SCRA) is pivotal for ensuring resilience in increasingly complex global supply networks. While existing reviews have explored traditional methodologie…
A Natural Language Processing-Based Classification and Mode-Based Ranking of Musculoskeletal Disorder Risk Factors
Md Abrar Jahin, Subrata Talapatra
This research delves into Musculoskeletal Disorder (MSD) risk factors, using a blend of Natural Language Processing (NLP) and mode-based ranking. The aim is to refine understanding…
Exploring Internet of Things Adoption Challenges in Manufacturing Firms: A Delphi Fuzzy Analytical Hierarchy Process Approach
Hasan Shahriar, Md. Saiful Islam, Md Abrar Jahin +4
Innovation is crucial for sustainable success in today's fiercely competitive global manufacturing landscape. Bangladesh's manufacturing sector must embrace transformative technolo…
Big Data$\unicode{x2013}$Supply Chain Management Framework for Forecasting: Data Preprocessing and Machine Learning Techniques
Md Abrar Jahin, Md Sakib Hossain Shovon, Jungpil Shin +2
This article intends to systematically identify and comparatively analyze state-of-the-art supply chain (SC) forecasting strategies and technologies. A novel framework has been pro…
QAmplifyNet: Pushing the Boundaries of Supply Chain Backorder Prediction Using Interpretable Hybrid Quantum-Classical Neural Network
Md Abrar Jahin, Md Sakib Hossain Shovon, Md. Saiful Islam +3
Supply chain management relies on accurate backorder prediction for optimizing inventory control, reducing costs, and enhancing customer satisfaction. However, traditional machine-…
DIT4BEARs Smart Roads Internship
Md Abrar Jahin, Andrii Krutsylo
The research internship at UiT - The Arctic University of Norway was offered for our team being the winner of the 'Smart Roads - Winter Road Maintenance 2021' Hackathon. The intern…