Danielle Belgrave facts for kids

Danielle Charlotte Belgrave is a computer scientist. She is from Trinidad and Tobago and Britain. Danielle works at DeepMind. She uses statistics and machine learning to understand how diseases change. This helps scientists learn more about health.

Early Life and School

Danielle grew up in Trinidad and Tobago. Her high school math teacher inspired her. This teacher helped her want to become a data scientist.

She studied statistics and business. This was at the London School of Economics (LSE). She then went to University College London (UCL). There, she earned a master's degree in statistics.

In 2010, Danielle moved to the University of Manchester. She earned her PhD there. Her research was supported by a scholarship from Microsoft. She also won two awards for her studies. These were the Dorothy Hodgkin award and the Barry Kay Award.

Research and Career

After finishing her studies, Danielle worked at GlaxoSmithKline (GSK). She received an award there for being an "Exceptional Scientist."

In 2015, Danielle joined Imperial College London. She worked as a statistician for the Medical Research Council. She creates special computer models. These models help her understand how diseases progress. This can lead to new ways to manage illnesses.

Understanding Diseases

Danielle uses her models to find "endotypes." These are hidden types of a condition. She looks at different symptoms, called "phenotypes." Her models help group people with similar disease patterns. This helps doctors understand conditions better.

She studied how allergic diseases develop in children. This is sometimes called the "atopic march." She looked at over 9,000 children. Her machine learning models found groups of children. These groups had similar patterns of eczema (a skin condition).

Danielle is part of a team studying early life asthma. She wants to use large amounts of data. This data can help doctors give personalized advice. It can help prevent diseases for each person.

Using AI in Healthcare

Her research focuses on using Bayesian and statistical machine learning. This helps create personalized medicine. Personalized medicine means treatments are made for each person.

As of 2019, Danielle is working on new methods. These methods combine expert knowledge with data. Her research looks at many areas. These include how data changes over time. She also studies how to group similar data.

Danielle is also part of a project. It looks at how healthcare computer programs should be regulated. She is interested in who should be responsible for these programs. She helps organize important computer science conferences. She also advises an organization called DeepAfricAI.