‘Pattern formation in heterogeneous balancing spiking neuron network’
Yifan's research asks how the brain works, by reverse-engineering it from the bottom up, using large scale simulation and theoretical analysis. His software allows Yifan and his colleagues to efficiently simulate a very large network of neurons using supercomputers, looking at the collaborations between excitatory and inhibitory neurons to understand how the brain establishes balance.
Yifan Gu is a degree-qualified Aerospace engineer, who was drawn to a PhD program in theoretical physics in University of Sydney by the opportunity to work on the single most complex dynamical system in the universe: the human brain. He is a firm believer of the motto “What I cannot create, I do not understand” and has passionately joined the scientific endeavour of reverse-engineering the brain, one neuron at a time (the human brain has 100 billion neurons). In particular, Yifan's research focus is on the collaborative behaviour of neurons emerging from the intricate balance established in a complex network, which could lead to new insights into the origin of intelligence.