Danielle Belgrave is a Principal Research Manager in the Healthcare Intelligence group at Microsoft Research, in Cambridge (UK). She leads Project Talia, which aims at using machine learning to understand how we can improve mental health. Her main research interests are in probabilistic graphical modelling and causal modelling frameworks to identify subtypes of disease, in order to help develop personalized treatment and intervention strategies. She obtained a BSc in Mathematics and Statistics from London School of Economics, an MSc in Statistics from University College London and a PhD in the area of machine learning in health applications from the University of Manchester. Prior to joining Microsoft, she was a tenured Research Fellow at Imperial College London.

Laura Weidinger is a Research Scientist on the DeepMind Ethics & Society team, investigating different topics on the Ethics of Artificial Intelligence. Previously, Laura studied mechanisms of human learning at the Max Planck Institute for Human Development in Berlin and at University College London. Before that, Laura worked as policy adviser for a tech industry association in London and on EU policy in Brussels. Laura holds a BA in Politics, Psychology and Sociology from University of Cambridge and an MA in Neuroscience and Philosophy from the Berlin School of Mind and Brain at Humboldt University Berlin.

Marta Garnelo is a research scientist at DeepMind working on deep generative models and meta learning. During her time at DM she has worked on Generative Query Networks as well as Neural Processes and recently her research focus has shifted towards multi-agent systems. In addition, she is currently in denial about having to wrap up her PhD with Prof Murray Shanahan at Imperial College London.