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About Me

Hi, my name is Danielle Belgrave. I am a machine learning researcher based in London, UK. Explore this website to find out more about my research.


My Research

I am VP of Artificial Intelligence/ Machine Learning at GSK AI where I lead a team focused on the development of novel AI approaches for advancing drug development and clinical applications. Prior to joining GSK, I led multiple research teams and projects across academia and industry including DeepMind, Microsoft Research, Imperial College London and The Univrestity of Manchester. My research focus for more than 15 years has been on developing machine learning strategies for personalising healthcare interventions. The basis of this research is in combining data-driven and hypothesis-driven approaches to understanding disease heterogeneity and understanding different subtypes of disease. A list of my publications in advancing the field of machine learning for healthcare, particularly applied to respiratory health, mental health, and understanding causality of disease, can be found here.  


I have degree in business and statistics from the London School of Economics and a master’s degree in statistics from University College London. My PhD was at the University of Manchester in Machine Learning for Healthcare, supported by a Microsoft Research scholarship and a Dorothy Hodgkin postgraduate award. During this time, I also received the Barry Kay Award from the British Society of Allergy and Clinical Immunology (BSACI).

In 2015, I joined Imperial College London as faculty and I received the highly prestigious and competitive Medical Research Council Award in Biostatistics (4 years funding). During my time at Imperial, I developed statistical machine learning models to look at disease progression in an effort to design new management strategies and understand heterogeneity in asthma and allergic diseases.

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