Our research underpins many seemingly unrelated real-world applications through fundamental modelling and optimal processing of signals. Understanding the early universe through cosmic background radiation, medical image synthesis and analysis of the human brain, and planetary science have in common signals that can be represented on a sphere and processed optimally by exploiting their inherent structures. We conduct fundamental research on spherical signals to propose novel models and methods that can deal with very large data sets and enable real-time low-complexity processing of such signals.
For better understanding of biological systems and processes, we identify and optimise signal processing model parameters from both natural and synthetic data measurements. Through theoretical and computer modelling, we can accurately predict and improve the behaviour of natural and artificial biological systems and agents, limiting the need to conduct expensive in-vivo and in-vitro experiments.
We also develop unique signal processing techniques for data communications over wired and wireless networks. Our focus is on improving signal transmission and reception techniques to enable the optimal use of limited system resources such as energy, bandwidth, and computational power and memory.
Explore our available student research projects below and if you’d like to discuss opportunities for collaboration or funding, please email us.
|Code||Title||Semester||Offered in 20'||Course convener|
|ENGN4536||Wireless Communications||S2||18, 19, 20||Dr Nan Yang|
|ENGN2228||Signal Processing||S2||18, 19, 20||Prof Xiangyun (Sean) Zhou|
|ENGN2218||Electronic Systems and Design||S1||18, 19, 20||Assoc. Professor Salman Durrani|
|ENGN3213||Digital Systems and Microprocessors||S1||18, 19, 20||Dr Jon Kim|
|ENGN3226||Digital Communications||S1||18, 19, 20||Prof Xiangyun (Sean) Zhou|