Personalised digital health

In collaboration with RowAnalytics Ltd, this project will build an, IoT enabled, intelligent patient monitoring and response system, where complex edge analytics and disease knowledge models are combined with a patient’s health data to provide fully personalized real-time advice. The student will leverage our previous successes in deep reinforcement learning for real-time control problems to develop new learning architectures that will allow fast convergence of networks despite the presence of non-stationarity. The complexity introduced by the highly non-stationary sensor inputs will be reduced with state of the art probabilistic models. At the same time the student will extend our deep reinforcement learning transfer work in a multi-agent setting. We envision that this will empower seamless cooperation and coordination in distributed sensor and actuator networks, ultimately leading to efficient decision-making in these challenging decentralised settings.
Collaborator: RowAnalytics Ltd

Further information: https://jobs.aston.ac.uk/Vacancy.aspx?ref=R190206