The Tissue Image Analytics (TIA) Centre hosts a seminar series for those interested in computational pathology. The series invites researchers and leaders in computational pathology and related fields to present their work and foster thought-provoking discussions.

This seminar features Dr Danielle Belgrave, GSK, London, UK.

Abstract

Multimodal machine learning models can learn shared representations of human biological state from molecular, cellular, imaging, and clinical data to better understand disease mechanisms. These models are applied across clinical development to support biomarker discovery, patient stratification, and treatment response. Our work aims to build scalable AI to enable precision medicine.

Bio

Danielle Belgrave is a VP of AI/ML at GSK. Her experience spans conducting machine learning research and leading teams across academia and industry focused on scientific discovery and personalising interventions in health. She has previously worked at Google DeepMind, Microsoft Research Cambridge, UK and Imperial College London. She has a BSc in business mathematics and statistics from the London School of Economics and a master’s degree in statistics from University College London. Her PhD was at the University of Manchester in Machine Learning for Healthcare.