About the project
There is a growing demand for high-throughput and low-power signal processing in implantable devices. Traditional DSP engines struggle with this need, while compact AI models can offer better accuracy with smaller code sizes. Efficient implementation on silicon can allow small components to run effective machine learning algorithms with minimal power use.
The project has the following three objectives:
- To architect and prototype network topologies tailored to large-scale deep learning driven signal processing algorithms. Novel topologies are supposed to provide load-aware distributed processing on the network, while enabling sustainable energy management.
- To implement and validate the operation of the introduced networks in step (1), using FPGA. This step further helps translation of a FPGA design on silicon in a specific complementary metal-oxide-semiconductor (CMOS) technology (e.g. 180 nm).
- To benchmark energy, performance and accuracy against the state-of-the-arts. Our interest is to develop designs utilizing the steps (1) and (2) for real-time and on-chip classification of biomedical signals, however, other applications can be identified. For example, we have already developed complex algorithms for implantable brain-computer interfaces that can be translated into hardware using the proposed flow for low-power and sustainable uses.
You will have the opportunity to learn many desirable knowledge and scientific skills during this PhD.
You will have a chance to training and networking opportunities offered through the CDT and to collaborate with a strong multidisciplinary team of academics at the University of Southampton.
There are also opportunities to work in the state-of-the-art laboratory facilities within the School of Electronics and Computer Science (DHBE and SET) and Zepler Institute.
Applicant will be provided with access to MATLAB, FPGA board, Cadence software and fabrication facilities.
The School of Electronics and Computer Science is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
