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.
- 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.
- Nanoscale interfaces – developing interfaces between conventional electronics and nanoscale devices
Collaborators
Our collaborators include:
- The EPSRC Centre for Doctoral Training in High Performance Embedded and Distributed Systems (HiPEDS) at Imperial College http://hipeds.doc.ic.ac.uk
- The School of Electrical Engineering and Automation at Harbin Institute of Technology http://en.hit.edu.cn/sSchool.asp?id=245