Trustworthy and explainable AI for smart energy system management

Location:

Engineering Department, Streatham Campus, Exeter

The University of Exeter’s Department of Engineering is inviting applications for a PhD studentship fully-funded by the University to commence on 8 January 2024 or as soon as possible thereafter. For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £18,622 for 3.5 years full-time, or pro rata for part-time study. The student would be based in the Faculty of Environment, Science and Economy at the Streatham Campus.

Project Description:

Decarbonisation of the energy system is key to combatting climate change and achieving a net-zero (NZ) future. The 2018 IPCC report highlights the climate emergency and criticalness of achieving a NZ greenhouse gas future to limit future temperature rise to 1.5C. Buildings are responsible for 30% of greenhouse gas emissions like carbon-dioxide and 40% of the total energy consumption and hence a large contributor to global warming. At the same time, building occupants spend 90% of their time in indoor spaces, raising the need to maintain indoor air quality within acceptable ranges due to a strong correlation that exists between carbon dioxide levels and occupants’ health, well-being, and productivity. The smart building concept has been recognised by the research community as one of the key approaches to make buildings energy efficient, healthy, comfortable and places where productivity and talent cultivation is encouraged.

In this context, AI has been seen as a key enabling technology to realise the vision of the digital smart buildings and bring significant benefits to the smart control and optimisation of the integrated building systems by seamlessly resolving the complex interactions between indoor air quality, thermal comfort, energy consumption, and space utilisation. However, although there are many research papers of applying AI and data science to the building sector, there are only limited real-world practical applications in the industry: i.e., there is a big gap between academic research and practical deployment. One of the reasons for this is that most of the current deep learning-based AI algorithms are black boxes and lack transparency and explainability, hence seriously limiting their use in critical infrastructures such as buildings. This PhD project aims to address this issue by applying explainable and trustworthy AI methodology and framework to smart energy systems to make step changes in this area.

The studentship will be awarded on the basis of merit for 3.5 years of full-time study to commence on 8 January 2024.

International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.

For Further information & to apply please use this link - Award details | Funding and scholarships for students | University of Exeter