Research
My research combines explainable AI, predictive modelling, and decision-support systems to address challenges in healthcare, operations, and financial crime detection. As a Research Assistant at UEL, I work on applied healthcare AI, with wider interests in NLP and computer vision. My upcoming PhD focuses on AI-driven fraud detection.
Research Interests
- Explainable AI
- Interpretable Machine Learning
- Predictive Modelling
- Decision-Support Systems
- Healthcare AI
- Operational Analytics
- Financial Crime Analytics
- Fraud Detection
- FinTech
- Natural Language Processing
- Computer Vision
- Deep Learning
- Neural Networks
- Human-Computer Interaction
- Public-Sector AI
- Multimodal Learning
- Anomaly Detection
- Sentiment Analysis
Recent Research Milestones
Fully Funded PhD
Awarded a UEL scholarship for doctoral research on AI and financial crime detection.
ISADES 2026
Presented a workforce-aware AI framework for NHS emergency admission and delay prediction.
Knowledge Exchange Project
Contributed to funded UEL research addressing avoidable hospital readmissions and healthcare service efficiency.
PCCDA 2026
Service-delay prediction research accepted for conference publication and presentation.
Healthcare & FinTech Workshops
Shared research on explainable healthcare AI and financial crime detection with academic and external partners.
Freshwater Fish Image Dataset
Co-authored a Data in Brief publication supporting fish species identification research.
Published Papers
Network Traffic Anomaly Detection using Deep Learning and Explainable AI
IEEE Xplore
Read paper ↗A Transformer Based Approach for Analyzing Scrapped E-Commerce Product Reviews from Social Media Platforms with Explainable AI
IEEE Xplore
Read paper ↗Comprehensive Smartphone Image Dataset for Fish Species Identification in Bangladesh’s Freshwater Ecosystems
Data in Brief · Vol. 61, Article 111629 · Elsevier
Read paper ↗Optimized Deep Learning Approach for Accurate Poultry Disease Detection
Springer
Read paper ↗Hybrid Deep Learning Approach for Accurate Fish Species Recognition in Bangladeshi Markets
IEEE Xplore
Read paper ↗A Deep Learning Approach to Recommending Undergraduate Programs for Bangladeshi Students
IEEE Xplore
Read paper ↗Deep Learning Approach for Multi-Label Detection of Abusive Bangla Social Media Comments
IEEE Xplore
Read paper ↗Soft Voting Ensemble-Based Approach for Diagnosing Diabetes Mellitus
IEEE Xplore
Read paper ↗Bangla E-Commerce Sentiment Analysis Optimization Using Tokenization and TF-IDF
IEEE Xplore
Read paper ↗Accepted Papers & Presentations
An AI-Driven Workforce-Aware Framework for Emergency Admission and Delay Prediction in NHS Emergency Care
ISADES 2026
An Explainable AI Decision-Support Framework for Operational Delay Prediction: Evidence from Restaurant Data
PCCDA 2026
Bangladeshi Plant Leaf Freshness and Disease Detection Using Deep Learning
ECCE 2025
Ongoing Research
Healthcare Decision Support
Applied AI research at UEL on emergency care, patient flow, and avoidable hospital readmissions, supervised by Dr. Fahimeh Jafari.
Financial Crime Detection
Fully funded doctoral research at UEL on AI-driven fraud detection in partnership with the FCA, supervised by Dr. Fahimeh Jafari and Dr. Michael Harrison.
Auditable ESG Reporting
From Fragmented Records to Auditable ESG Reporting: Design and Preliminary Evaluation of an Integrated Accountability Platform for Hospitality SMEs.
Audio Deepfake Detection
Word-Level Multimodal Learning for Audio Deepfake Detection and Robust Speaker Identification.
Emergency Admission Delay Prediction
Predicting Admission Delays in the NHS Emergency Departments Using Hybrid Deep Learning and Workforce Metrics.
Explainable Healthcare Prediction
Predicting Emergency Admission Delays in NHS Hospitals: An Explainable ML Approach Using Real-World Workforce and Patient Data.
Unplanned Hospital Admissions
Understanding Healthcare Services Through Professional Perspectives to Minimize Unplanned Admissions.