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Personal profile

Research interests

The heart of my research interests lie in understanding how cells in different areas of the brain orchestrate their activity to communicate with one another, and are therefore able to form the basis of complex thoughts and actions.

Inter-area communication: My research focuses on understanding how information flows through the brain. While there are many potential models for this, here are two that I have focused on:

  • Eye-hand coordination relies on a network of brain areas specialised to guiding eye movements and arm movements that must work together with high temporal precision. Eye-hand coordination is a complex behaviour that has been extensively studied by psychologists, and therefore is ideal for testing hypothesis on how brain areas communicate.
  • Visual information is processed through a hierarchical network of brain areas. Each area up the hierarchy carries out more complex computations on visual information to ultimately form our rich perception of the world. The individual areas of the hierarchy have been extensively studied, but little is known about how information is transformed from one stage to the next. Therefore, the visual hierarchy is ideal for studying hypothesis about feedforward processing in the brain.
  • Attention and decision-making are examples of complex, cognitive behaviours that are achieved via the interactions of networks of brain areas in the frontal and parietal cortices. By studying single or multiple nodes in this network, we can understand how information flows through the brain to guide complex behaviours.

Neural engineering: Understanding how areas of the brain communicate with one another has many practical applications such as the development of brain-machine interfaces that can be used to restore function or faculty lost by accident or disease.

Computational neuroscience: My work generates large, complex datasets. Increasingly, our ability to analyse and understand these data relies on computational methods and modelling. Computational models help us to fill in the gaps of experimental data and generate new hypothesis about underlying neural mechanisms.





B.S, Neuroscience, University of California Los Angeles 2006

PhD, Neural science, New York University 2013


Monash University

Brain Networks and Behaviour Lab, Lab Head




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