Biography:
Danielle Charlotte Belgrave is a Trinidadian-British computer scientist based at DeepMind, who uses statistics and machine learning to understand the progression of diseases. Belgrave grew up in Trinidad and Tobago, where her high school mathematics teacher inspired her to work as a data scientist. She pursued her passion by studying statistics and business at the London School of Economics (LSE). Belgrave then went on to become a graduate student at University College London (UCL), where she earned a master’s degree in statistics.
In 2010, Belgrave moved to the University of Manchester to pursue her PhD. Her research was supervised by Iain Buchan, Christopher Bishop, and Adnan Custovic. During this time, Belgrave was supported by a Microsoft Research scholarship and was awarded a Dorothy Hodgkin postgraduate award by Microsoft, as well as the Barry Kay Award by the British Society of Allergy and Clinical Immunology (BSACI).
After completing her studies, Belgrave joined GlaxoSmithKline (GSK), where she received the Exceptional Scientist Award. In 2015, she joined Imperial College London as a Medical Research Council (MRC) statistician. In her role, she develops statistical machine learning models to analyze disease progression in order to design new management strategies and gain a better understanding of heterogeneity. Belgrave’s work focuses on using statistical models to identify the underlying endotypes of a condition from a set of phenotypes. Her research has contributed to our understanding of atopic march, the progression of allergic diseases from early life, and its relation to conditions like eczema. She has utilized machine learning to identify different patterns of eczema onset in over 9,000 children, which has provided valuable insights into atopic diseases.
Belgrave is also part of the study team for the early life asthma research consortium. Her research interests extend to using big data for meaningful clinical interpretation, with the aim of informing personalized prevention strategies. She is particularly interested in Bayesian and statistical machine learning within the healthcare field to develop personalized medicine. Currently, Belgrave is focused on developing and implementing methods that incorporate domain knowledge with data-driven models.
Outside of her research, Belgrave is involved in the regulatory algorithms project, which evaluates how healthcare algorithms should be regulated. She is specifically interested in determining what scheme of liability should be imposed on artificial intelligence in the healthcare sector. Belgrave serves on the organizing committee of the Conference on Neural Information Processing Systems and is an advisor for DeepAfricAI.
Awards:
– Dorothy Hodgkin Postgraduate Award by Microsoft
– Barry Kay Award by the British Society of Allergy and Clinical Immunology (BSACI)
– Exceptional Scientist Award at GlaxoSmithKline (GSK)