A Kingston University London academic has been awarded a prestigious Leverhulme Trust Research Fellowship by the Royal Academy of Engineering to develop innovative quantum artificial intelligence (AI) technologies that could improve the design of sustainable energy-harvesting devices.

Senior Lecturer in Computer Science Dr Xing Liang, who is also Founder and Head of the Quantum AI (QAI) Research Group in the School of Computer Science and Mathematics, is one of just eight researchers across the UK to receive the fellowship this academic year.

The Fellowships, supported by the Leverhulme Trust, allow awardees to focus on full-time research for up to a year by covering the costs of a replacement academic to take over their teaching and admin duties. This allows mid-career engineers to reinvigorate their research interests and give junior academics an opportunity to gain valuable teaching and administrative experience by stepping in for the duration of the award.

Dr Liang’s award will support her research into the application of quantum AI to sustainable energy technologies.

Her project, Quantum AI-Driven Energy Harvesting from Cavitation Devices, aims to address a key challenge in small-scale sustainable energy generation – designing efficient devices that can capture energy associated with the formation and collapse of tiny bubbles in rapidly flowing liquids. Known as cavitation, this phenomenon offers potential opportunities for energy harvesting, as well as applications in water treatment, chemical processing and drug delivery.

As demand grows for sustainable power sources for sensors, portable electronics and off-grid systems, researchers are exploring innovative methods of generating energy at small scales. However, cavitation is a highly complex physical process, making it difficult to predict how different device designs will perform and to optimise their energy-harvesting efficiency using conventional approaches.
To overcome these challenges, Dr Liang will develop a hybrid quantum–classical machine learning approach that combines AI with quantum computing techniques. By analysing key device characteristics, including the geometry and shape of microchannels, the research aims to predict device performance and identify more effective designs, reducing reliance on costly and time-consuming trial-and-error experimentation.

The project could accelerate the development of more efficient and cost-effective energy-harvesting devices, supporting new approaches to sustainable power generation for small-scale and off-grid technologies. Beyond energy generation, the quantum AI methods developed through the research could also contribute to the optimisation of other cavitation-based technologies and wider engineering applications.

Commenting on the award, Dr Liang said: “I’m delighted and honoured to receive a 2026 Royal Academy of Engineering / Leverhulme Trust Research Fellowship. This award will enable me to advance my research in quantum AI for sustainable energy harvesting, and I’m grateful to the Royal Academy of Engineering, the Leverhulme Trust, research collaborators and my colleagues at Kingston University London for their support.”