Developing Foundation Models for Spatial Biology
- Generating diverse, high-quality datasets to train robust AI models and overcome challenges in data access, annotation, and standardisation
- Improving interpretability and clinical validation of deep learning models to build trust, reproducibility, and regulatory readiness
- Leveraging foundational and multimodal AI tools to streamline image analysis, and enhance spatial data interpretation