Building explainable, clinically meaningful AI for medical image analysis.
I'm an AI researcher working on medical imaging at Canterbury Christ Church University, where I'm completing an MSc in Data Intelligence alongside a research placement. My current work centres on pancreatic CT analysis and 3D segmentation with Vision Transformers, and on making those models explainable enough for clinicians to trust. Ten peer-reviewed papers so far.
Research Assistant (Placement) & MSc Data Intelligence student
Nazmul Hasan Shouvo
Research, at a glance
Current focus
Pancreatic CT and 3D segmentation
Deep learning and ViT-based approaches, medical-image preprocessing, model evaluation, and publication-oriented research.
Pancreatic CT preprocessing view for the current research workflow. demo
Explore research
Latest publication
Class-Weighted ResNet50 for Robust Guava Leaf Disease Classification under Real-Field Conditions
Grad-CAM overlays on misclassified guava leaves, field-condition subset. demo
Read the record →
Peer-reviewed
10
publications
Accepted / in press
3
book chapters
Teaching at CCCU
AI, data intelligence, and foundations
Guest lecturer and teaching assistant across Python, Linear Algebra, Probability, and research methodology.
Research interests
Artificial IntelligenceMachine LearningDeep LearningMedical Image AnalysisExplainable AI (XAI)3D Medical Image SegmentationVision TransformersAI for HealthcareTrustworthy AI
