I am an AI researcher focused on deep learning for medical image analysis, with a particular interest in neurodegenerative disease detection, MRI-based classification, and Explainable AI (XAI) for clinical applications.
My research sits at the intersection of multi-view learning, 3D volumetric segmentation, and multimodal architectures — building systems that are not only accurate but interpretable enough to be trusted in a clinical setting. I am actively working toward a Master's / PhD in AI or Medical Imaging.
Rahim, N., Ahmad, N., Ullah, W., Bedi, J., & Jung, Y. (2025). Early progression detection from MCI to AD using multi-view MRI for enhanced assisted living. Image and Vision Computing, 105491.
Q1 Journal · Top 10% in Field · Impact Factor 4.2 · Elsevier
Developed a multi-view deep learning framework for detecting early progression from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) using multi-modal MRI data, with explainability mechanisms to support clinical decision-making.
| Area | Tools & Technologies |
|---|---|
| Languages | Python · Java · C++ |
| Deep Learning | PyTorch · TensorFlow · Keras · Hugging Face |
| Medical Imaging | MONAI · OpenCV · SimpleITK · NIfTI/MRI pipelines |
| ML / CV | Scikit-learn · Transfer Learning · Model Fine-Tuning · Image Processing |
| XAI | Grad-CAM · Feature Attribution · Saliency Maps |
| CS Fundamentals | Data Structures · Algorithms |
| Tools | Git · GitHub · Linux (Ubuntu) · Kaggle · Google Colab · Jupyter |
🧠 Neurodegenerative Disease Detection (Alzheimer's, MCI)
🏥 Medical Image Analysis & MRI Classification
🔍 Explainable AI (XAI) for Clinical Applications
🌐 Multimodal AI & Vision-Language Models
📐 Multi-view & 3D Volumetric Deep Learning
⚗️ Model Interpretability & Trustworthy AI
BSc Computer Science · Abdul Wali Khan University Mardan, Pakistan
Sep 2019 – Sep 2023
- 🏆 Q1 Journal Publication — Image and Vision Computing, IF 4.2, Top 10% worldwide (2025)