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Self-Adaptive Performance Assurance for AI Systems

   School of Science

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  Dr T Chen, Dr Lin Guan  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

This project offers the chance to take part in work that will have real world impact, e.g., potential to help engineers to build better software systems that impact millions. You will work with world-leading experts in their field and become part of the IDEAS lab - a group of researchers working on the intersection between Software Engineering and Artificial Intelligence. The group has monthly meetings and thus you will have strong interaction with the other PhD students.

Loughborough University is a top-ten rated university in England for research intensity (REF, 2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.

In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career. 

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Artificial Intelligence (AI) systems are prevalent in our daily life. Yet, challenges remain for their performance assurance due to the high dimensionality/scale of those systems (e.g., many options to tune), expensive measurements (e.g., taking hours/days to train), and the uncertainty on the operating environment (e.g., poor generalisation). This project seeks to investigate a self-adaptive approach that intelligently optimises/tests the performance (e.g., speed, accuracy, and resource computation) of AI systems at various levels and granularities, considering the fidelity, uncertain constraints, and the environments under which they will operate.

The ultimate goal is to equip current AI systems with the ability of “cognitive self-adaptation”, so that they behave, just like human, to consistently achieve the best of their performance in daily work. To that end, the student will investigate novel approaches, such that the characteristics and expert knowledge of the domain can be fully exploited, taking some domain-specific “simplified shortcuts” to improve the result with less overhead. The student will evaluate the approach on real-world open-source AI systems/frameworks that are widely used.

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Entry requirements for United Kingdom

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Computer Science, Software Engineering, Artificial Intelligence or a related subject. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: performance engineering, machine learning, metaheuristics algorithms. You will also be hardworking, a good communicator, good at working as part of a team, can bring new perspectives and learn new knowledge. We welcome applications from under-represented categories.

Please see the programme website for international entry requirements by country.

English language requirements

Applicants must meet the minimum English language requirements. Further details are available on the International website.


All applications should be made online at Under programme name, select 'Computer Science'

Please quote reference number: TC/CO/2022

Funding Notes

Please note that studentships will be awarded on a competitive basis to applicants who have applied to this project and other advertised projects within the School. Funding decisions will not be confirmed until early 2022. The studentship is for 3 years and provides a tax-free stipend of £15,609 per annum for the duration of the studentship plus tuition fees at the UK rate. International (including EU) students may apply however the total value of the studentship will cover the International Tuition Fee Only.
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