PhD researcher in Medical Sciences (AI in Oncology) at the University of Cambridge, working at the Cancer Research UK Cambridge Institute.
Building and stress-testing multimodal AI systems that combine histopathology, genomics, and patient data to improve early cancer diagnosis and clinical safety.
Interested in computational biology, AI governance, and trustworthy clinical machine learning with a focus on interpretability, reproducibility, and responsible deployment.
email: rehanzuberi@icloud.com
linkedin: rehanzuberi
Developing generalist ML models to track live cell images:
- Developing a Napari plugin to track static cells and match them
- Developing a U-Net model to distill CellPose2
- Model to segment cells and attempts to classify static cells into their cell cycle phase