The Computer Engineering Lab develops novel hardware and software techniques to solve computationally intensive problems.

Research areas include:

  • Reconfigurable Computing – studying how field programmable gate array (FPGA) devices can be utilised to solve previously intractable problems in signal processing, mathematics and financial engineering; embedded systems hardware; and developing improved FPGA architectures for domain-specific applications.
  • Machine learning – mainly parallel and real-time machine learning applications in the following areas:
    • Financial Engineering – applying parallel processing in the form of clusters, multicore, manycore and graphics processing units to real-time and large-scale machine learning problems in derivative pricing and foreign exchange risk.
    • Biomedical Engineering – lung function, cardiology and movement disorders.
  • Nanoscale interfaces – developing interfaces between conventional electronics and nanoscale devices


Our collaborators include: