The recent breakthrough in designing customized neuromorphic chips capable to compute complex neural algorithms and the better understanding of the biological olfactory mechanisms offer the perfect starting point for investigating new neuromorphic algorithms for reconfigurable software-hardware heterogenous platforms with applications in artificial olfaction. The research will explore computational models capable to deploy many parallel computing cores in low cost heterogeneous multiprocessor system on chip platforms and cope with the smell recognition challenges that arise in the very short transitional olfaction signals measurements done in noisy environmental conditions.  The project seeks to achieve ultra-rapid olfaction measurements with possible applications in health monitoring and 3D plume odorant mapping.

The increasing of elderly population requires a rise in the provision of specialised support services. This provision is putting existing resources under strain as the support requirements for the elderly grow. The dramatic change in human interaction and behaviour triggered by the recent pandemic outbreak has imposed general social distancing, forcing seniors to stay in their own homes whenever possible. The research will explore the development of an end-to-end system, based on a distributed computing paradigm for non-invasive detection of abnormal ambient phenomena (characterised by acoustic, olfaction and electromagnetic signals) to provide an effective care monitoring and decision-making service for domestic environments.

The research prioritizing the end-user programming (EUP) concepts when designing hardware implementable neural networks. The work builds on the research done on developing FPGA libraries from the hardware designer’s point of view by implementing an interdisciplinary approach (hardware design – end-user programming) on increasing the programming level, via an intuitive and interactive EUP interface based on semantic rules, abstractions and representations, expert system, and GUI event-based architecture.

To apply for an MSc by Research or PhD within the Reconfigurable System on Chip are, please email the coordinator, Dr Alin Tisan at alin.tisan@rhul.ac.uk with details about your research interests as well as a summary of your academic qualifications (a brief one to two page CV will be useful) and if you are self-funded or require funding. After you have liaised with Dr Alin Tisan you will be able to register an account on Royal Holloway Direct to formally submit your application.

More details on the application process can be found here.