Start Date:1 October 2021
Supervisors: John McAllister (EEECS) and Pantelis Sopasakis (EEECS) In mobile autonomous devices systems such as robots, vehicles or sensing equipment, the need to survive on battery power makes low power operation essential. This is motivating entirely new computing approaches, such as neuromorphic devices whose behaviour mimics that of the brain. There has been an explosion of interest in how approaches such as spiking neural networks (SNNs) can be used to enable processing and cognitions in such systems due to their ability to offer similar features to deep learning with much lower power costs. These advantages make SNNs extremely promising approaches for autonomous devices.
There remain significant challenges in the design of SNNs-based solutions for autonomous data processing. Outstanding issues include efficient algorithms for SNN-based data processing, synthesis of SNN models which achieve specific behaviours, low-cost solutions on programmable hardware devices such as Field Programmable Gate Array, event-driven hardware architectures, and many others. This project will address this problem with a focus on autonomous robots.
•Develop an understanding of the behaviour, key operations and network structure of neuromorphic computing techniques.
•Devise custom neuromorphic systems for the three applications.
•Study techniques for automatic synthesis of SNN models.
•Create demonstrator systems showing the effectiveness of the resulting solutions.
The School of Electronics, Electrical Engineering and Computer Science (EEECS) aims to enhance the way we use technology in communication, data science, computing systems, cyber security, power electronics, intelligent control, and many related areas.
You’ll be part of a dynamic doctoral research environment and will study alongside students from
over 40 countries worldwide; we supervise students undertaking research in key areas of electronics and
electrical engineering, including: power electronics,robotics, wireless communications, cybersecurity and sensor-based systems. As part of a lively community of over 100 full-time and part-time research students you’ll have the opportunity to develop your research potential in a vibrant research community that prioritises the cross-fertilisation of ideas and innovation in the advancement of knowledge.
Within the School we have a number of specialist research centres including a Global Research Institute, the Institute of Electronics, Communications and Information Technology (ECIT) specialising in Cyber Security, Wireless Innovation and Data Science and scalable computing.
Many PhD studentships attract scholarships and top-up supplements. PhD programmes provide our students with the opportunity to acquire an extensive training in research techniques.
Research students are encouraged to play a full and active role in relation to the wide range of research activities undertaken within the School and there are many resources available including:
Access to the Queen's University Postgraduate Researcher Development Programme
A wide range of personal development and specialist training courses offered through the Personal Development programme
Office accommodation with access to computing facilities and support to attend conferences for full-time PhD students
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