AI researcher working at the intersection of deep learning, computer vision, and medical imaging.
I have hands-on experience building and deploying AI systems for:
- Medical image segmentation, detection, and classification
- Opportunistic disease screening and risk stratification (CVD, oncology)
- CT, X-ray, MRI, and ultrasound analysis using deep learning
My research focuses on translating theory into practice—developing
data-efficient, scalable, and clinically meaningful models.
I’ve worked across the full pipeline, from model design and experimentation
to real-world deployment (DICOM workflows, APIs, end-to-end systems).
Most repositories here contain research code, experiments, and reproducible pipelines supporting published and ongoing work.
- Medical image analysis and representation learning
- Weakly supervised & foundation-model-based learning
- Survival analysis and imaging-based risk prediction
- Model interpretability and robustness in healthcare AI
Python · PyTorch · TensorFlow · Keras · FastAI
OpenCV · SimpleITK · Scikit-image · Pydicom
Linux · Docker · Git · REST APIs