My PhD focuses on how cooperative behaviour between agents is shaped by the environment. By understanding how different incentives give rise to different system dynamics, I aim to be able to design mechanisms that will promote pro-social behaviour. My project utilises theoretical and experimental techniques from areas such as game theory, economics, evolutionary computing and reinforcement learning.
Before joining the CDT, I worked as a research scientist in Machine Translation. I decided that I would like to be involved with AI in a more fundamental way. I believe that there is a good chance that AI will transform society in the coming decades, and I would like to spend my career working to mitigate the risks and maximise the benefits associated with the increasing utilisation of AI. The CDT is well aligned with my interests and exposes me, through the work of fellow students and professors, to many different approaches that people are taking to tackle these issues.
Undergraduate Qualification: BA Physics Oxford
Masters Qualification: MSc Applied Mathematics Imperial