Associate Professor Jonathan Shock

Research Interests

My research covers Machine Learning, Physics, Neuroscience and Mathematics Education. On the machine learning side, I am interested in how multiple, artificial agents can learn to coordinate in complex environments, as well as studying the role of affect in artificial agents who need to balance competing needs. I also use machine learning methods to study the brain age trajectory.

On the physics side, I undertake research in theoretical particle physics, as well as tracking algorithms for fluid dynamics.

On the mathematics education side, I undertake research in understanding how to overcome the gap between high school and university level mathematics.

Research Areas

Cognitive and Behavioural Neuroscience • Neuroimaging • Computational Neuroscience