Biography

I grew up in Toronto, Canada and did my undergraduate and masters degree at the University of Cambridge, studying engineering and specialising in computer and information engineering. During my degree, I became interested in artificial intelligence and machine learning, especially the biological basis for learning. In neuroscience, there are computational analogues in machine learning algorithms to what is observed in biology, such as the reward prediction error theory and reinforcement learning. During my PhD at the MRC Laboratory of Molecular Biology in the neurobiology division, I seek to understand the behaviour of dopamine neurons and the neural circuits that regulate these activities, using the Drosophila larva as a model system. With this research, we can gain insight, through new developments in connectomics, the circuit basis for learning, which can inform us about biologically-inspired methods in machine learning. I hope to use these insights from biological experiments to understand the neurobiological basis for learning, as well as inspire new algorithms in machine learning and artificial intelligence. This can in turn help us postulate new theories for how learning occurs biologically.

Previous Education

University of Cambridge Engineering Tripos 2022